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Spatial order and social position: Neighbourhoods, schools and educational inequality

Sykes, B.

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Brooke Sykes Spatial Order and Social Position: Neighbourhoods, Schools and Eduactional Inequality

Thursday, 10 February 2011, 12.00 hrs in the Agnietenkapel, Oudezijds Voorburgwal 231, Amsterdam. 10 February 2011, 12.00 hrs in the Agnietenkapel, Oudezijds Voorburgwal Thursday, are warmly welcome to attend a reception afterwards. You Brooke Sykes You are cordially invited to attend the public defense of my doctoral dissertation You Spatial Order and Social Position: Neighbourhoods, Schools Educational Inequality Paranimfen: Anna Glasmacher & Jen Kowalski Brooke Sykes Invitation SPATIAL ORDER AND SOCIAL POSITION: NEIGHBOURHOODS, SpatialSCHOOLS Order AND and Social Position: EDUCATIONAL INEQUALITYNeighbourhoods, Schools and Educational Inequality .

Brooke SykesBrooke Sykes Spatial Order and Social Position: Neighbourhoods, Schools and Eduactional Inequality Thursday, 10 February 2011, 12.00 hrs in the Agnietenkapel, Oudezijds Voorburgwal 231, Amsterdam. 10 February 2011, 12.00 hrs in the Agnietenkapel, Oudezijds Voorburgwal Thursday, are warmly welcome to attend a reception afterwards. You Brooke Sykes You are cordially invited to attend the public defense of my doctoral dissertation You Spatial Order and Social Position: Neighbourhoods, Schools Educational Inequality Paranimfen: Anna Glasmacher & Jen Kowalski Brooke Sykes Invitation ISBN: 978-94-90371-66-1 Layout and printing: Off Page, www.offpage.nl Cover design and illustration: Wolfgang Philippi (www.wolfgangphilippi.de) Proofreading: Zoe Goldstein ([email protected]) Copyright © 2011 by B. Sykes. All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without prior permission of the author. ([email protected]) SPATIAL ORDER AND SOCIAL POSITION: NEIGHBOURHOODS, SCHOOLS AND EDUCATIONAL INEQUALITY

ACADEMISCH PROEFSCHRIFT

ter verkrijging van de graad van doctor aan de Universiteit van Amsterdam op gezag van de Rector Magnificus prof. dr. D.C van den Boom ten overstaan van een door het college voor promoties ingestelde commissie, in het openbaar te verdedigen in de Agnietenkapel op donderdag 10 februari 2011, te 12.00 uur

door

BROOKE SYKES geboren te Petrolia, Canada Promotiecommissie

PROMOTOR: Prof. dr. S. Musterd

CO-PROMOTOR: Dr. H. Kuyper

Overige leden: Prof. dr. R. Andersson Prof. dr. S. Karsten Prof. dr. J.J. Latten Prof. dr. C.H Mulder Prof. dr. M.P.C van der Werf

Faculteit der Maatschappij- en Gedragswetenschappen

1 Introduction: Theory, research and policy context

1 Introduction There is a common notion that growing up in a poor neighbourhood presents a number of challenges that individuals in economically better-off areas are less likely to encounter. This belief influences social policymaking, families’ residential decisions and social science research. In recent years, the notion of a ‘neighbourhood effect’ has received significant attention in the academic and policy world. Scholars examining neighbourhood effects investigate the links between place of residence and individual outcomes and trajectories, such as labour market status, health and wellbeing, and educational career. This field of research recognizes that resources and opportunities are not distributed evenly across geographic space and that these spatial inequalities may be implicated in the reproduction and reinforcement of social inequalities. Residential patterns of poverty, affluence and socioeconomic status are often discussed in terms of the level of segregation. At the most general level, segregation refers to the degree to which two or more groups who differ across certain criteria (e.g. social class, ethnicity) are separated from each other across spatial or organizational units (e.g. neighbourhoods). Patterns of neighbourhood segregation, as well as other social differences between groups and individuals, are reflected in the school system; thus, people also speak of ‘segregated schools’. Intersecting questions about the effects of neighbourhood and school composition, particularly social and ethnic segregation in these settings, are important and recurring topics in political and academic discussions (Furstenberg and Hughes, 1997; Karsten et al., 2006; Latten, 2005; Musterd, 2003). This dissertation sheds light on these questions by examining the educational outcomes of youth in the Netherlands in relation to their neighbourhood and school contexts. This book consists of five separate studies that deal with different facets of the broader academic and political debate on the implications of neighbourhood and school composition. Bringing together bodies of literature on neighbourhood effects, school effects, residential and school segregation, and youth education, this book aims to contribute to the debate on the role of the neighbourhood in shaping individual outcomes, and particularly to the understanding of the interplay between youth, neighbourhoods and schools. While there is widespread agreement that geography is relevant for understanding social relations and inequalities, just how important one’s residential context is for shaping their opportunities and life chances, understanding through which mechanisms the neighbourhood matters, and deciding upon how to conceptualize and measure ‘neighbourhood effects’, are subjects of ongoing debate. Although the notion

Introduction 13 of neighbourhood effects appeals to our common sense understanding that places offer different social opportunities, the story is more complex than often assumed and adapting the framework of neighbourhood effects to policy is a contentious matter. In the remainder of this chapter, I introduce the theoretical framework and conceptual model underpinning this book. I first outline the thesis of neighbourhood effects and juxtapose it with broader geographical theory on socio-spatial relations. I then connect the notions of neighbourhood effects and school effects, and consider the theoretical and conceptual links between neighbourhoods, schools and youth. Following this, I discuss the research design and research questions addressed in this study and introduce the content of the following chapters.

Conceptualizing ‘neighbourhood’ 1.1 and ‘neighbourhood effects’ What is a neighbourhood? What are ‘neighbourhood effects’? These two questions are not as straightforward as they might seem and are not always elaborated in studies of neighbourhood effects, so it is worth examining them closely here. Neighbourhoods are at once spatially and socially constituted areas, embedded in city, metropolitan and (inter)national contexts. Neighbourhoods are ‘multiply constructed’ – they may be defined and named by officials, but are also defined, interpreted and imagined in multiple ways by different groups and individuals (cf. Gieryn, 2000; Martin, 2003). Thus, the precise definition of a neighbourhood is not self-evident, nor is there one way that it can be defined or operationalized in research. Two people living on the same block or even in the same house can have a different view of what constitutes their neighbourhood (e.g. Burton and Price-Spratlen, 1999; Lee and Campbell, 1997). Moreover, peoples’ spatial sense of neighbourhood is likely to vary depending on the activity in question (e.g. using local facilities versus greeting neighbours), and to expand and contract over time (e.g. over age and life stage). Likewise, the neighbourhood of interest to researchers also varies depending on the research questions and topic of investigation. Those examining the outcomes of neighbourhood regeneration programmes are apt to focus on the neighbourhoods officially designated as regeneration areas, while those investigating local interpersonal relations may focus on much smaller, subjective neighbourhood spaces. The slipperiness of the neighbourhood concept and the constraints in defining and operationalizing it for empirical research have been widely recognized (e.g.

14 Chapter 1 Andersson and Musterd, 2010; Chaskin, 1997; Kearns and Parkinson, 2001; Martin, 2003; Lee and Campbell, 1997; Lupton, 2003; Pebley and Sastry, 2004). Martin (2003: 362) writes, “we do not know neighborhoods when we see them; we construct them, for purposes of our research or social lives… The neighborhoods that we define through research or social exchange are always subject to redefinition and contention; they are not self-evident”. Many qualitative studies apply a fluid definition of neighbourhood; however, larger-scale quantitative studies are more restricted in their operational definitions and usually adopt administratively delineated (or other predefined) areas as neighbourhood proxies. While these areas might resonate with what some inhabitants perceive to be their neighbourhood, and may correspond to ‘official’ (e.g. municipal government-defined) neighbourhoods, they are understood to be proxies for a persons’ residential context. In contrast to communities, neighbourhoods are necessarily geographical (i.e. spatial) areas; thus, a neighbourhood is, broadly speaking, a geographical area in which residents share proximity and the circumstances that come with that proximity (Chaskin, 1997; Martin, 2003). Many ‘places’ are nestled within a neighbourhood (Reay and Lucey, 2000); thus a neighbourhood can be seen as a set of places, each of which has linkages to other places. In neighbourhood effects research, the neighbourhood is often viewed as a mediating link between the macro and the micro (Gotham, 2003). It is these macro-to-micro relationships which Wilson (1987, 1996) sought to document in his well-known work on the south side of Chicago: economic restructuring, deindustrialization and middle-class suburbanization resulted in the departure of low-skilled jobs and middle-class families from the inner-city (for him, a protective ‘social buffer’ for the urban poor), bringing about, he argued, worsening conditions for those living in poor urban neighbourhoods. Neighbourhoods have material (e.g. streets, buildings, physical space) and social (e.g. social and cultural milieu) elements, although it is mainly, but not exclusively, the social that is of interest to neighbourhood effects researchers. It is recognized, however, that the social and material are related (e.g. physical features, such as shared housing entryways, dense high rises or the presence of parks, could facilitate or hinder social interaction). The notion of neighbourhood effects draws on the idea that where we live influences who we meet, how we view the world (and how the world views us), the resources and opportunities available to us, and ultimately, our chances in life. Whether neighbourhoods matter in general (or whether ‘place matters’) is not really at stake. As geographers frequently point out, social life necessarily occurs in certain spaces and places, and space is “one of the axes along which we experience and conceptualize the world” (Massey, 1994: 251). The

Introduction 15 neighbourhood, as one such social and material space, can thus have salience for how we experience, understand and perceive the world. Neighbourhoods matter for young people because, for many, they will be where their first friendships are formed and where they attend primary school. For some, they will be sources of identification and social belonging (e.g. Wridt, 2004). Even as children grow up and eventually move away from home, their childhood neighbourhoods may remain strongly implanted in their memories (L. Karsten, 2010; Valentine, 2003). The issue, rather, is that residence in certain neighbourhoods – as areas with differing population constellations, reputations, and allocations of institutional resources, services and facilities – might promote or undermine one’s wellbeing and life chances. The question, as it is often expressed in the literature, is whether neighbourhoods matter for one’s life chances over and above other factors known to be important for individual outcomes, such as social class, family circumstances and gender. Referring to neighbourhood and school contexts, Duncan and Raudenbush (1999: 29) write that “context can be said to matter if differences among social contexts are found to be important in explaining individual differences in achieving ends most of us value – mental health, literacy, intellectual growth, educational attainment, occupational status, and the like”. Some researchers have formulated the question of neighbourhood effects as “do poor neighbourhoods make their residents poorer?” (Friedrichs and Blasius, 2003: 808), or by the argument that “it is worse to be poor in a poor area than one that is socially mixed” (Atkinson and Kintrea, 2004: 438). Other scholars have pointed out that these types of notions do not adequately capture the interconnectedness between people and place – the fact that ‘people make places, just as places make people’ (e.g. Burton and Price-Spratlen, 1999; Furstenberg and Hughes, 1997; Smith and Easterlow, 2005). Social class and family circumstances may also be related to neighbourhood conditions, and people do not come to live in neighbourhoods through random processes. If people and place are intertwined, can we determine the ‘effects of neighbourhoods’? Thinking about the connections between space and society from a causal perspective, Gans (2002: 330) poses two questions: “[f]irst, do both natural and social space have causal power, creating social effects, and if so when, how, and why? The second question reverses the causal arrow: Do individuals and collectivities exert causal power, creating effects on both kinds of space, and if so, when, how, and why?” He writes that the answer to both questions is yes – “individuals and collectivities shape natural and social space by how they use these, although each kind of space, and particularly the social, will also have effects on them” (ibid.) – but that the effects of space are not automatic and usually work indirectly. He is essentially describing the mutual constitution of

16 Chapter 1 space and society: a continuous two-way relationship between social processes and spatial form (and between spatial processes and social form) (cf. Massey, 1984; Soja, 1980). Individuals imprint themselves on and modify their spatial world, while their (socio-)spatial surroundings also influence them. The thesis of neighbourhood effects draws mainly on this latter idea: that where we live helps to shape our attitudes, activities, behaviour and opportunities. A child’s behaviour, worldview, aspirations and life chances will in part be shaped by the places they live, by the structures, friends, schoolmates, adults, institutions and agencies they encounter in their everyday surroundings. In terms of the reciprocal relationships between people and space/place, neighbourhood effects research is most directly concerned with the neighbourhood à individual relationship. The fact that social forces produce and reproduce uneven geographies is implicit in neighbourhood effects research; the main goal of which is to determine how much (and how) these (unequal) residential environments bear upon individuals (and their behaviour, opportunities and life chances). Thus, the ‘neighbourhood’ may have effects – or more concretely, the social relations and processes, institutions and agencies related to it or embedded in it – may have effects, but the social actions of entities such as individuals and groups also shape what the neighbourhood is and what goes on in and around it. The thoughts of geographer Doreen Massey (1984: 4-5; emphasis in original) are helpful:

What does it mean to say that space has effects? One thing it does not mean is that ‘space itself’, or particular spatial forms, themselves have effects… It is not spatial form in itself (nor distance, nor movement) that has effects, but the spatial form of particular and specified social processes and social relationships.

One of the main reasons why researchers investigate neighbourhood effects is the concern that inequalities across neighbourhoods may perpetuate social inequalities. Processes of social and spatial inequality are generally understood to be causally intertwined (Soja, 1980; Massey, 1984). Social inequality refers to the disproportionate allocation of resources and the unequal access to opportunities among different individuals or groups in society. The study of spatial inequalities recognizes that geography can be a salient source of social inequality: where people are located in geographic space matters. Social inequalities may be articulated spatially; for example, in residential patterns marked by divisions in income, class and race. Residential segregation may be a spatial expression of

Introduction 17 social inequality, although it need not be1. At the same time, spatial patterns help to reproduce or exacerbate social differences. Thus, spatial patterns, created through social processes and unequal power relations, may simultaneously or in turn contribute to unequal social outcomes. Massey (1984: 4) argues that if spatial patterns (e.g. of poverty, privilege, unemployment, deprived or affluent neighbourhoods) are seen only as a reflection or outcome of social processes, this presents an important conceptual problem, for “[t]here is more to it than that. Spatial distributions and geographical differentiation may be the result of social processes, but they also affect how those processes work. ‘The spatial’ is not just an outcome; it is also part of the explanation”. Thus, there may be explanatory power in the ‘neighbourhood’, but it is, obviously, only part of the explanation. This is an important point, because the causes of social problems are increasingly traced back to local characteristics (cf. Amin, 2007; Fallov, 2010; Goetz, 2010; Lupton and Tunstall, 2008). Amin (2007: 105) argues that “social inequality has come to be re-cast as a defect of place, a deficiency of the capacity of local residents to participate and connect, resulting in social breakdown, de-motivation and isolation”. Commenting on current neighbourhood regeneration policies, he remarks, “[o]vercoming inequality has become a matter of community mobilization and bridging social difference (e.g. through mixed housing, ethnic dialogue, multicultural spaces) rather than one of tackling systemic and trans-local sources of injustice”. Fallov (2010) makes a similar point in her analysis of Danish and British neighbourhood and social exclusion policies that aim to cultivate local ‘community capacities’ and ‘neighbourhood-wide social capital’, which are presented as effective means of tackling social exclusion. The danger of this kind of discourse is that individual social problems become rendered as neighbourhood phenomena, and the underlying causes of the problems are lost. This perspective can thus obscure the wider structural forces that help to create and perpetuate neighbourhood inequalities, and shape the social circumstances of the people living in the neighbourhood. As Musterd (2002: 140) remarks, although social problems may become manifest in a neighbourhood, this does not imply that they are caused by the neighbourhood or its population composition. Thus, while processes and conditions associated with a neighbourhood may help to aggravate or reinforce social problems (though also conversely, to reduce, alleviate and reshape them), the underlying sources of social problems such as poverty and ethnic inequality

1 Residential segregation can also occur, for example, when groups segregate for reasons such as solidarity and maintaining cultural identity and community (Peach, 1996; Musterd, 2003).

18 Chapter 1 lie elsewhere. Neighbourhoods cannot be divorced from the broader systems and forces that penetrate and shape them2.

1.2 Literature and research findings Over the past two decades, the study of neighbourhood effects has generated a vast and interdisciplinary interest, with studies spanning the disciplines from sociology (Ainsworth, 2002; Small and Newman, 2001), criminology (Oberwittler, 2004; Sampson et al., 2002), geography (Musterd and Andersson, 2005; Pinkster, 2007; Smith and Easterlow, 2005), health studies (Diez Roux, 2004; Macintyre et al., 2002), economics (Oreopoulus, 2003), family and child studies (Burton and Price-Spratlen, 1999), to psychology3 (Leventhal and Brooks-Gunn, 2000). This research has examined the associations between neighbourhood conditions and individual outcomes such as educational career and school aspirations, youth delinquency and crime, family management and parenting strategies, stress and mental health, and labour market outcomes. Much of the impetus behind this work has been the notion that to understand how people and their social circumstances are shaped and conditioned necessitates consideration of their spatial contexts. Without taking features of both people and the places they inhabit into account, we have only a partial account of their experiences; for instance, the risks and opportunities they encounter, and how their wellbeing may be promoted or constrained. From the side of policymaking, knowledge about residential inequalities and the effects of neighbourhood conditions is presumed to aid in the development of geographically-targeted policies and programmes (cf. Forrest and Kearns, 2001). Widespread interest in the neighbourhood resurged across the social sciences in the late 1980s, due in large part to the work of Wilson (1987) on the causes and consequences of concentrated inner-city poverty. In the late 1980s, there was a recognition that poverty in the US had become much more spatially concentrated, and a perception that social problems in poor neighbourhoods had worsened. Wilson argued that in addition to institutional and geographical constraints, such as the ‘spatial mismatch’ between low-income individuals and employment and educational opportunities, processes such as role modelling, shared values and social norms made living in a neighbourhood with many

2 These points are elaborated in Chapters 5 and 6. 3 And indeed, many studies cut across several of these disciplines (e.g. Furstenberg et al., 2000).

Introduction 19 disadvantaged people more challenging than elsewhere. His work prompted a ‘rediscovery of the neighbourhood’ (Small and Newman, 2001) across the social sciences – in the US and abroad – and turned scholarly, media and political attention towards the dynamics of neighbourhood poverty. A second theoretical framework that helped to turn attention towards the neighbourhood, particularly in research concerned with children and youth, stems from developmental psychology. Bronfenbrenner’s (1981, 1989) ‘ecological systems theory’ (or ‘development in context’) advocated a better appreciation of the role of context in development4. A fact that had gone unrecognized in much of the literature on development was simply that development could not occur without a context. In addition to the family, Bronfenbrenner outlined how extrafamilial contexts, including the school and neighbourhood, were important settings for understanding individual wellbeing and trajectories. His model of ecological systems describes the individual as a member of a series of interconnected and overlapping contexts, from the proximal family context to the more distal city and national contexts. While individual and family characteristics (e.g. social class, access to economic, cultural and social capital, and family structure) are important for understanding individual outcomes, he stressed that families and individuals are also situated in, and react to, the wider neighbourhood and community settings. Research findings, based on both quantitative and qualitative methods, have resulted in a substantial base of evidence underlining the role of the neighbourhood in various facets of individuals’ lives. This research has elucidated both the complex and subtle ways in which place of residence may be important for individual decisions and life chances. Studies have documented the uneven ‘geography of opportunity’ and its relationship to youths’ perceptions and choices about work and education (Galster and Killen, 1995), and the ways in which families manage risks in their local environments while raising children (Furstenberg et al., 2000). Quantitative studies have documented the long-term implications of childhood neighbourhood segregation for future educational outcomes (Andersson and Subramanian, 2006; Massey and Fischer, 2006) and earnings (Galster et al., 2007). Qualitative research and neighbourhood case studies have delved more deeply into the specific processes and pathways that may link one’s behaviour and outcomes to their residential surroundings, including local social networks and prevailing norms about work (Pinkster, 2007), school ‘gatekeeping’ practices

4 Despite a different disciplinary tradition than Wilson and the other urban scholars usually associ- ated with the study of neighbourhood effects, Bronfenbrenner’s ideas have been highly influential in neighbourhood effects research on children and youth (e.g. Brooks-Gunn et al., 1997; Chase- Lansdale et al., 1997; Furstenberg et al., 2000; Rankin and Quane, 2002; Galster and Santiago, 2006; Leventhal and Brooks-Gunn, 2000; Leventhal et al., 2009).

20 Chapter 1 that work to limit the school choices of youth from certain stigmatized areas (Warrington, 2005), and neighbourhood-contingent institutional practices that affect youths’ career development (Bauder, 2002).

The social and institutional 1.3 mechanisms of neighbourhood effects Two of the major tasks of neighbourhood effects research have been determining the nature and relative importance of neighbourhood effects (i.e. how much does residential location matter?), and explaining how these effects come about (i.e. untangling the processes or mechanisms driving neighbourhood effects). The intervening processes posited to connect children, youth and adults’ behaviour and outcomes to their residential contexts have been linked to a number of social-interactional and institutional mechanisms, including institutional resources (e.g. the presence, quality and diversity of public services, local schools, health facilities), local social relations, collective socialization (e.g. adult monitoring and supervision), peer relations, parenting and family functioning, social norms and collective efficacy (i.e. conditions of mutual trust, shared expectations among residents), and stigmatization (e.g. negative stereotyping of neighbourhoods) (Jencks and Mayer, 1990; Sampson et al., 2002; Galster et al., 2007). It is also important to note that not all of these mechanisms depend on residents having face-to-face contact or even being aware of each other. While neighbourhood youth may communicate with each other directly and interact in that manner (i.e. peer relations), the processes driving neighbourhood effects could also be a function of external factors, for example, the government or market allocation of institutions, facilities and other resources based on composition of the neighbourhood, which in turn bear upon individual residents. Some residents, for instance, might be more likely or better equipped to advocate for the neighbourhood and its institutions and services (e.g. schools and school quality, parks, public infrastructure, safety and policing) and to command the attention of government or political actors (Joseph et al., 2007). These residents are usually thought to be those with more financial or social investments in the neighbourhood (e.g. through home ownership or longer term residence) and with access to relatively more resources (e.g. resourceful social networks, time, cultural capital). Thus, through both internal (e.g. collective social functioning) and external (e.g. stigmatization, public service allocation) processes, neighbourhood conditions are thought to have an effect on individual wellbeing and opportunities. As mentioned above, these are not simply deterministic or

Introduction 21 one-way effects; people are in constant dialogue with their surroundings and the effects of the neighbourhood are moderated by personal characteristics and circumstances. Many of the ideas about the mechanisms of neighbourhood effects are apparent in policy documents. For instance, a recent large-scale, area-based programme of the Dutch Ministry of Housing, Neighbourhoods and Integration aims to improve the social conditions in what it deems the 40 most socially troubled districts in the country5. The policy text links multiple social problems to neighbourhood composition (VROM, 2007: 4):

Many neighbourhoods have an overrepresentation of socially disadvantaged households. For the most part, these neighbourhoods also have a disproportionately high proportion of non-Western immigrants. The lack of relevant skills and poor prospects for employment ensures that these groups in these neighbourhoods take part less and less in Dutch society, which in some cases is coupled with resentment towards society… Middle-income groups move away to other, better districts or neighbouring municipalities, while, at the same time, lower-income and underprivileged groups move in or stay behind… The function of the city as an emancipation machine for low-income groups and immigrants therefore comes under pressure. It is not uncommon that the best teachers, who are precisely needed at schools in these districts, leave for schools in better neighbourhoods, because the working circumstances there are less difficult (ibid.)6.

Middle- or higher-income residents are often (implicitly or explicitly) presumed to be a resource for the neighbourhood and its residents, as are good teachers (who may, according to the policy text, be attracted to economically better- off neighbourhoods or deterred from teaching in socially disadvantaged neighbourhoods). There does appear to be some support for the notion that schools in poor districts have more difficulty recruiting and retaining teachers7. Karsten et al. (2006) find indications of what they term ‘teacher flight’ in Amsterdam. Primary schools serving large shares of children from low-

5 The ‘Actieplan Krachtwijken’ (Powerful Communities Action Plan); also called the ‘40 Districts of Vogelaar’. 6 Translated from Dutch. 7 However, this is presumably due to a more complicated set of factors – including inadequate teacher training or experience in teaching children who are not proficient in the language of instruction, or who have related learning challenges – rather than inherently difficult working circumstances (see Gewirtz, 1998; Lupton, 2005).

22 Chapter 1 socioeconomic status and non-Western immigrant backgrounds had the greatest share of teacher vacancies, while secondary schools offering vocational tracks of education (which serve a disproportionate amount of students from low- socioeconomic and immigrant backgrounds) had more difficulty filling vacancies than other schools (for supportive US findings, see Clotfelteret al., 2006; Scafidi et al., 2007). This Dutch social mixing policy and similar approaches are discussed further in Chapter 5.

Joining two strands of literature: The 1.4 residential and educational landscape Children and youth have held an important place in neighbourhood studies. The residential context is thought to be particularly relevant for them, as many spend a vast amount of their time there, attending local schools, playing with friends, and using nearby parks and services. Young peoples’ spatial range is also generally more restricted than that of adults, who have easier access to transportation, money and more freedom to travel (Matthews and Limb, 1999). Moreover, studies show that adults with children tend to maintain more relationships in their neighbourhood (e.g. Henning and Lieberg, 1996), so not only will children and youth have local relationships, but so will their parents. An important neighbourhood institution for many young people is the school. Neighbourhoods and schools are two interrelated spheres in the lives of young people, which often overlap as places of learning and socializing. We can think about the links between neighbourhood and school in a number of ways. The school can be seen as a local institutional resource that is, by nature of the educational quasi-market, unevenly accessible to all people and places. The geography of education provision is not equal. Some neighbourhoods have better schools, more schools, and as noted above, conditions that are more attractive to (highly qualified) teachers (Lupton, 2005; Karsten et al., 2006). As a local place frequented by many residents, the school is also a meeting place for children, youth and their parents (L. Karsten, 2007), and a place where friendship ties and social networks are formed and maintained. Especially for those children and youth who are educated locally, the school is a neighbourhood institution where they will spend a good part of their weekdays. In the neighbourhood effects literature, the school is considered to be a pathway through which the neighbourhood context may influence children and youth. Because residential patterns tend to inform local school populations, schools are places where young people come into contact with neighbourhood children and their families.

Introduction 23 The school is also a social context in its own right and not all students attend a neighbourhood school. Conceptually similar to the notion of ‘neighbourhood effects’ is the notion of ‘school effects’. School effects (or school composition) research investigates the implications of student body composition, often in concert with other school characteristics, for such outcomes as the achievements, friendships and school careers of students (Thrupp et al., 2002). Through the interrelated channels of peer group processes, teaching and instructional processes, and school organization and management, the composition of the student body is thought to have meaning for students’ outcomes. In this book, I bring these two fields of research together. Chapter 3 delves deeper into the meaning of school segregation for youth educational outcomes and briefly discusses the (asymmetrical) relationship between school and neighbourhood segregation. Chapter 4 examines the hypothesis that schools are a pathway through which neighbourhood conditions may indirectly influence young people.

The current study: Research approach 1.5 and conceptual model 1.5.1. Research questions In this book, I explore, through several avenues, the merits and limits of the neighbourhood effects approach to understanding the links between place of residence and youth educational outcomes. The questions that initiated this research are:

Can neighbourhood effects on youths’ educational outcomes be identified, and if so, what is the nature and extent of these effects? Are neighbourhood effects on youth transferred through the school context?

The neighbourhood effects that I am mainly interested in are those related to the social milieu of the neighbourhood, thus I investigate the associations between neighbourhood socioeconomic context (proxied by indicators such as the average neighbourhood income, rate of unemployment, share of low- and high-income households, share of homeownership) and youth educational outcomes. Before examining neighbourhood effects and school effects together, it was necessary to investigate school effects; thus, the following research question was also formulated:

24 Chapter 1 Does the socioeconomic or ethnic composition of the school have an effect on youths’ secondary school outcomes?

Figure 1 depicts the conceptual model underpinning this research, which is inspired by Smith and Easterlow’s (2005) model of area effects on health inequalities. The distinctive feature of their approach is that it takes the understudied reciprocal relationships between people and neighbourhoods into account. Starting with the left side of the figure, the ‘neighbourhood effects’ pathway is indicated by the arrow connecting ‘neighbourhoods’ to ‘youth’ by way of the box signifying the intervening mechanisms thought to drive neighbourhood effects. The arrow running next to this one, from ‘schools’ to ‘youth’, indicates the possible effects of the school context on youth (i.e. school effects). These relationships are examined in Chapters 2 and 3 respectively. The arrow running upwards from the ‘neighbourhoods’ to ‘schools’ box signifies the possible transfer of neighbourhood effects on youth through the school context, while the arrow running between the ‘neighbourhood effects’ and ‘school effects’ pathways indicates that these effects may also work mutually; these relationships are tested in Chapter 4. On the right side of the figure an arrow runs from ‘youth’ to ‘schools’ and ‘neighbourhoods’, indicating not only that youth make up part of these contexts, but also that they choose or are selected into these contexts, for example by their (and their families’) school and residential decisions. This depicts what is often described as ‘selection effects’ – the fact that individuals are not randomly sorted into neighbourhoods and schools (Dietz, 2002; Sampson et al., 2002). While youths’ parents clearly are the primary people making residential choices, youth

Figure 1. Relations between youth, neighbourhood and schools Figure 1. Relations between youth, neighbourhoods and schools

On the right side of the figure an arrow runs from ‘youth’ to ‘schools’ and ‘neighbourhoods’, indicating not only that youth make up part of these contexts, but also that they choose or are selected into these contexts, for example by their (andIntroduction their 25 families’) school and residential decisions. This depicts what is often described as ‘selection effects’ – the fact that individuals are not randomly sorted into neighbourhoods and schools (Dietz, 2002; Sampson et al., 2002). While youths’ parents clearly are the primary people making residential choices, youth typically have quite a large role in deciding which secondary schools they attend, and they can (consciously or unconsciously) shape how oriented they are towards their school and neighbourhood contexts through their decisions and actions concerning the friendships they maintain, their activities, the places they visit and hang out, whether they play indoors or outside in their neighbourhood, and, in the case of divorced or separated parents, how much time they spend living at each parents’ house, and so on8. While youth and their families can and do make these kind of decisions, the other half of the relationship is also relevant, for these decisions are made within the context of a set of constraints. For example, schools and neighbourhoods are not accessible or open to everyone; school practices and access rules regarding formal and informal admissions can exclude certain youth or deter them from attending (Warrington, 2005; Karsten et al., 2003; Noreisch, 2007). As Karsten et al. (2001) note, schools can adopt strategies to improve their reputation or position in the local market, with one such strategy being to ‘regulate’ school intake. Education and housing choices are made under market or quasi-market conditions in which individuals are not equal players. Thus, the left side of this graph shows ‘context effects’ or the context  youth relationship, while the right side examines youths’ routes into and impact on contexts, which is the youth  context relationship.

8 These examples are taken from the qualitative findings of this study, reported in Chapter 6. typically have quite a large role in deciding which secondary schools they attend, and they can (consciously or unconsciously) shape how oriented they are towards their school and neighbourhood contexts through their decisions and actions concerning the friendships they maintain, their activities, the places they visit and hang out, whether they play indoors or outside in their neighbourhood, and, in the case of divorced or separated parents, how much time they spend living at each parents’ house, and so on8. While youth and their families can and do make these kind of decisions, the other half of the relationship is also relevant, for these decisions are made within the context of a set of constraints. For example, schools and neighbourhoods are not accessible or open to everyone; school practices and access rules regarding formal and informal admissions can exclude certain youth or deter them from attending (Warrington, 2005; Karsten et al., 2003; Noreisch, 2007). As Karsten et al. (2001) note, schools can adopt strategies to improve their reputation or position in the local market, with one such strategy being to ‘regulate’ school intake. Education and housing choices are made under market or quasi-market conditions in which individuals are not equal players. Thus, the left side of this graph shows ‘context effects’ or the context à youth relationship, while the right side examines youths’ routes into and impact on contexts, which is the youth à context relationship.

1.5.2 Data resources and methods This research uses primarily quantitative research methods. All data analyses are based on a large-scale study in the Netherlands called the ‘Longitudinal Cohort Study in Secondary Education – Cohort 1999’ (in Dutch, the Voortgezet Onderwijs Cohort Leerlingen or, VOCL’99). Beginning in 1999, this study follows a cohort of students from their first year of secondary school (average age 13 years old) until they leave full-time education. From an initial sample of 246 schools, 126 schools participated in the study. All students who entered the first year of these schools in 1999 belong to the cohort, totalling 19,391 students; this sample represents 11 percent of the population that entered the first year of secondary school in 1999. The sample was constructed by Statistics Netherlands and has been found to be representative of schools and students in Dutch secondary education (van Berkel, 1999) and neighbourhoods in the Netherlands (Sykes and Kuyper, 2009). Kuyper et al. (2003) provide details about the sampling design and all variables in the dataset (those used in the current study are also described in more detail in the following chapters).

8 These examples are taken from the qualitative findings of this study, reported in Chapter 6.

26 Chapter 1 Using students’ postcodes, I matched each student in the VOCL’99 dataset to a neighbourhood identifier, which was then matched to a national database with neighbourhood characteristics, published by Statistics Netherlands. In this way, I could see the characteristics of both youths’ neighbourhoods and schools. Neighbourhoods in this study are operationalized as the lowest administrative spatial subunit in the Netherlands (in Dutch, buurten). These areas vary in terms of number of inhabitants and surface area and tend to reflect natural borders, such as roads, rail- and waterways, parks, and building styles and periods. Nationwide, there were 10,737 of these neighbourhoods in 1999, with a mean population of 1468. Students in the VOCL’99 sample lived in 2248 (21 percent) of these neighbourhoods. Because of the structure of this dataset – individuals nested in neighbourhoods and schools – this study uses multilevel modelling and cross-classified modelling techniques. These techniques are a variation of standard (OLS) regression and are useful for analysing hierarchical data, as they take the non-random independence of two individuals in the same context (e.g. two students in the same school) into account and allow for estimation of variance at each level in the model. Multilevel modelling is used to estimate the associations between youth school outcomes and (separately) their neighbourhood and school contexts. Cross- classified models, which take into account the membership of individuals in two, non-nested units, are employed to test for the simultaneous associations between youth and their school and neighbourhood contexts. In addition to these large-scale (quantitative) studies, I conducted a small-scale qualitative study, in which in-depth interviews were carried out with 16 youth who grew up in Amsterdam. The purpose of these interviews was to gain a better understanding of the interactions between youth, schools and neighbourhood contexts, youths’ routes into their educational and neighbourhood settings, and their subjective interpretations of and experiences in their neighbourhoods. In these interviews I explored the varying definitions of neighbourhood that youth offer and their views on neighbourhood structure.

1.5.3 Caveats and strengths Specific strengths and limitations of the methodologies employed are discussed in the relevant chapters, but it is important to outline some key points here. First, the kind of modelling adopted in this study, as in all data modelling, rests on a number of assumptions and is obviously not a perfect conceptualization of the ‘real world’ or the real world relationships between youth and their school and neighbourhood settings. The effects estimated using these models must be read in the statistical sense, not the causal. Quantitative models can determine

Introduction 27 associations between variables and these variables can register (quantifiable) change, however “[i]nferring causality is a much more complicated process and requires more than statistical models” (Diez Roux, 2004: 1954; see also Sayer, 1992: 179). Thus, the neighbourhood and school effects estimated in the models must be interpreted as predictive and suggestive, rather than causal. While some of the data in the VOCL’99 is longitudinal (i.e. youths’ school outcomes), it was only possible to obtain cross-sectional information about youths’ neighbourhoods. Thus, the neighbourhood data represents a snapshot of youths’ residential contexts, rather than how these contexts changed over time. The operationalization that I use for youths’ neighbourhoods in Chapters 2 and 4 is based on administrative subunits, which is likely to underspecify youths’ actual neighbourhood contexts. Research suggests that different neighbourhood scales are relevant for different people, social activities and outcomes of interest, making the operationalization of ‘neighbourhood’ an ongoing complexity. The benefit of this approach is that I am able to comment on the magnitude and extent of associations between youth educational outcomes and neighbourhood conditions using a large, nationally representative dataset. While research in the Netherlands has examined neighbourhood effects on adult outcomes, such as social mobility (Musterd et al., 2003), dimensions of ethnic integration (van der Laan Bouma-Doff, 2007) and labour market behaviour (Pinkster, 2007), few studies have focused on children and youth, and no large-scale studies have examined neighbourhood effects on youth outcomes. Thus, this methodology is an important starting point. Moreover, the neighbourhood units used in this study do have political and social relevance; for example, they are often the targets of area-based initiatives and other neighbourhood policies, as well as the level at which certain public services are delivered and consumed. Defining ‘school’ and specifying it for research is more straightforward than specifying the neighbourhood context, thus the analyses of school effects have some advantages in this regard. Importantly, I measure neighbourhood and school conditions with quantitative data (e.g. mean household income, mean school socioeconomic status). This does not shed light on the real processes underlying the observed relationships between youth and their schools and neighbourhoods; I touch upon these issues in Chapter 6 and also by referring to the findings of other studies and the theoretical literature. Another methodological and conceptual challenge that neighbourhood effects (and other context effects) researchers must grapple with is the issue of selection bias – i.e. the fact that people are not sorted randomly into neighbourhoods (or schools or peer groups, etc.). Although often treated as a statistical nuisance, it is increasingly acknowledged that selection processes (e.g.

28 Chapter 1 how people are non-randomly and unequally sorted/selected/included/excluded into and from neighbourhoods and schools) are fundamental social processes and of substantive interest in their own right (e.g. Smith and Easterlow, 2005; Sampson and Sharkey, 2008). Indeed, this non-random sorting and selection is one of the main interests of researchers investigating school choice and admission processes (Ball et al., 1996; Saportio and Lareau, 1999) and residential choices and mobility (Croft, 2004; Mulder, 2007; Zorlu and Latten, 2009). Ultimately, neighbourhood effects research needs to better understand how and why people come to be in certain neighbourhoods, in order to understand the potential impact of these places. This issue is discussed further throughout the book.

1.5.4 Outline of the book Each chapter in this book has been written as a separate journal article and therefore there is some overlap in the description of the dataset and the theoretical background. In Chapter 2, I use multilevel modelling to estimate neighbourhood effects on youths’ school achievement in order to assess the potential for the neighbourhood context to affect individual school outcomes in the Netherlands. This analysis forms the starting point of this study, as it gives a first indication of how much variation in young people’s educational achievement exists between neighbourhoods, as well as an indication of the magnitude of the associations between youths’ residential contexts and their educational outcomes. Before examining neighbourhood and school effects together, Chapter 3 turns to the school context for an examination of the meaning of school segregation for youths’ educational achievement and school careers. This chapter is concerned with the relationships between school segregation and observed inequalities in educational outcomes across ethnic groups. The differentiated school performance of different (social and ethnic) groups raises questions about school conditions which might be unfavourable for students’ educational development. School segregation is seen as potentially being one of these conditions. This chapter also briefly discusses the drivers of school segregation and the relationship between neighbourhood and school segregation. Chapter 4 tests the hypothesis that the school is a pathway of the neighbourhood’s influence. A growing number of studies recognize that examining neighbourhood and school effects together is a necessary step towards better understanding the role these contexts play in the lives of young people. The analysis in Chapter 4 aims to better understand the possible links between neighbourhood and school effects, and specifically to test whether the influence of youths’ neighbourhood environments might be confounded by or transferred through the school context, suggesting the school’s role as an institutional

Introduction 29 mechanism of the neighbourhood effect. As the literature describes several possible relationships between neighbourhoods and schools and their potential effects on youth, I also test for moderating or interaction effects between these two contexts. Chapter 5 examines the policy context of neighbourhood effects research – specifically, how the idea of neighbourhood effects relates to policy efforts to restructure neighbourhoods into ‘socially mixed communities’ or ‘mixed income neighbourhoods’ – and discusses some of the limitations and caveats of the neighbourhood effects framework and social mixing initiatives. Scholars point out that much of the research on neighbourhood effects and the effects of concentrated poverty has advanced the notion that living among poor people perpetuates individual poverty, whereas middle-class neighbours provide benefits. Neighbourhood effects discourse has been invoked by policymakers to both define the ‘problem’ (i.e. socially unbalanced neighbourhoods) and justify the ‘solution’ (i.e. policy efforts to intervene in the social makeup of poor neighbourhoods). These issues and their potential implications for neighbourhood effects research are discussed in this chapter. Chapter 6 is dedicated to the qualitative interviews. This chapter constitutes an effort to conceptualize both parts of the individual ßà context relationship by discussing how youth shape their relationships with and experiences in their neighbourhoods and schools. I draw on youths’ descriptive accounts to show that neighbourhoods do have meaning for their everyday lives and longer-term outcomes, but that they are also active in choosing and interacting with the places they encounter, including their secondary schools and places within and beyond their neighbourhood. Finally, Chapter 7 concludes by summarizing the key findings of this book and revisiting the main research questions. I discuss the main findings of the book and the implications of these findings for future research. Methodologically and conceptually, I reflect on the usefulness of the neighbourhood effects framework for examining the role of (young) people’s residential contexts, and offer suggestions for how the framework might broaden to better take into account the dynamic and reciprocal relations between people and place. I suggest that the neighbourhood effects framework could be complemented and enriched by considering how neighbourhood space and neighbourhood social structure are produced and maintained. I conclude by offering suggestions for future research.

30 Chapter 1 References

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Introduction 33 2 Neighbourhood effects on youth educational achievement in the Netherlands Abstract

Adding to the growing body of research examining neighbourhood effects in European contexts, this study investigates the associations between the educational achievement of Dutch youth and their neighbourhood conditions. We further consider whether these associations vary by student socioeconomic status (SES), gender, or nativity. Results from a multilevel analysis of 17,836 secondary school students living in 3085 neighbourhoods, indicate significant relationships between several dimensions of the neighbourhood context and educational achievement. Student SES and nativity appear to moderate some of these effects. In particular, we find the negative effect of neighbourhood disadvantage to be almost entirely restricted to native youth. The achievement outcomes of students with higher levels of SES also appear to be less affected by neighbourhood affluence and disadvantage than those of lower-SES students. Our results suggest that the impact of neighbourhood conditions on certain groups of youth may be obscured in studies that measure average neighbourhood effects across all individuals. Future research which examines neighbourhood effects and mechanisms across subgroups of youth, and which examines the links between the neighbourhood, family, and school contexts, can help us to better determine the neighbourhood’s role in youth education.

Published as: Sykes, B. and Kuyper, H. (2009) ‘Neighbourhood Effects on Youth Educational Achievement in the Netherlands: Can Effects Be Identified and Do They Vary by Student Background Characteristics?’, Environment and Planning A, 41(10): 2417-36. © 2009 Pion Ltd.

36 Chapter 2 2.1 Introduction How people are shaped by the environments they live in has been an important and recurrent question in the social sciences (Park et al., 1925; Shaw and McKay, 1942; Wilson, 1987). Researchers from a range of disciplines have investigated whether individuals’ social, cognitive, health, and behavioural outcomes are influenced by the places in which they live. Children and youth have been the focus of much of this research, with educational outcomes being one of the key areas of interest (Ainsworth, 2002; Leventhal and Brooks-Gunn, 2000; Oliver et al., 2007). Neighbourhoods are thought to be particularly relevant for young people, as many spend a vast amount of their time there – residing, socializing with friends, participating in local activities, and often attending local schools and childcare centres. These children and youth will thus have numerous daily interactions with local peers, adults, and services; their behaviour, attitudes, and opportunities will be in part shaped in this setting (Bronfenbrenner, 1989; Brooks-Gunn et al., 1997). The present study adds to the fields of neighbourhood and educational research by examining the existence and nature of neighbourhood effects on youth educational achievement in the Netherlands. In this paper, we aim to assess the potential for the neighbourhood context to affect educational achievement in the Netherlands; to test whether certain neighbourhood conditions are associated with individual achievement; and to examine whether these associations vary across student SES, gender, or nativity. This paper makes several contributions. First, the Dutch context is an interesting setting in which to examine neighbourhood effects on education. In addition to a tradition of strong redistributive policies in the areas of housing and income, all schools (i.e. public, denominational, and those with a special pedagogical focus) are funded nationally on an equal basis, with a weighted-funding scheme allocating extra funds to schools with higher shares of disadvantaged pupils. Parents are also free (and obliged) to choose their child’s school, as there is no system of school catchment areas in the Netherlands. These factors – broad welfare redistribution, open school choice, and compensatory funding to schools – are interesting considerations in a study of neighbourhood effects on education, as they potentially reduce the likelihood of individual educational outcomes being linked to place of residence. Second, the focus is on an age group and outcome for which neighbourhood effects have been found in past North American (Ainsworth, 2002; Crowder and South, 2003; Leventhal and Brooks-Gunn, 2000) and European (Andersson, 2004; Kauppinen, 2007; McCulloch, 2006) studies, but which have received little attention in Dutch neighbourhood research. And third, a nationally

Neighbourhood effects on educational achievement 37 representative dataset is used, with individual, family, and educational information for around 18,000 students, or 10 percent of all Dutch students who entered secondary school in the school year 1999/2000. The nesting structure of students within neighbourhoods allows us to use multilevel regression analysis, which is generally a more accurate estimation of neighbourhood effects than traditional regression (Raudenbush and Bryk, 2002; Snijders and Bosker, 1999). The next section briefly reviews the mechanisms thought to drive neighbourhood effects on children and youth. Findings from European studies of neighbourhood effects on educational outcomes are then summarized, followed by a description of the current study’s research methodology and design. Results from a series of multilevel regression analyses are then reported, followed by a discussion of the findings and a conclusion.

How might the neighbourhood 2.2 influence youth? Wilson (1987) brought the issue of neighbourhood effects to the forefront in the US when he argued that living in a poor neighbourhood could exacerbate the effects of individual poverty. He saw things such as the shared norms, the level of parental monitoring and supervision, and the availability and quality of role models in a neighbourhood as potential means by which individuals could be negatively affected by their residential surroundings. Since his work, theoretical models have expanded to include potential beneficial neighbourhood effects, for example, those related to the presence of affluent neighbours, residential stability, or high levels of collective efficacy. While the immediate family is known to be the most important context for young people’s development and outcomes in general, it is increasingly acknowledged that individuals and families are situated in, and react to, broader neighbourhood and community structures and processes (Bronfenbrenner and Morris, 1998; Rankin and Quane, 2002; Sastry et al., 2006). The mechanisms connecting individuals’ and families’ behaviour and outcomes to their residential contexts have been linked to various school, peer group, individual- and neighbourhood- level processes. These mechanisms include the level of institutional resources in the neighbourhood (e.g. the presence and quality of local schools, parks, libraries, health services); collective socialization (e.g. adult monitoring and supervision, access to role models); peer relations (e.g. when language skills or attitudes towards schooling are affected by interaction with local peers); norms and collective efficacy (i.e. conditions of mutual trust, willingness to intervene for the common good, shared expectations among residents); and stigmatization

38 Chapter 2 (e.g. negative stereotyping of neighbourhoods by external actors) (Galster et al., 2007; Jencks and Mayer, 1990; Sampson et al., 2002). The role that parents and families can play in the transmission of neighbourhood effects to children and youth has also been highlighted (Kohen et al., 2008; Pinderhughes et al., 2001). Here, the notion is that children may be affected indirectly through the neighbourhood’s influence on parenting and family factors. In a longitudinal study of Canadian children, Kohen et al. (2008) identified effects of neighbourhood deprivation on family functioning and maternal emotional health, which in turn had consequences for children’s outcomes. They explain that “neighborhood-level economic and social hardship operate in a similar fashion to family-level disadvantage in creating conditions that stress the family unit and ultimately impact children” (ibid.: 164).

Youth education and neighbourhood 2.3 effects: European evidence Several decades of neighbourhood effects research in the US has provided a good deal of evidence that neighbourhood conditions matter for a variety of individual outcomes (Dietz, 2002; Leventhal and Brooks-Gunn, 2000; Sampson et al., 2002). Evidence of neighbourhood effects is thought to be particularly strong when educational outcomes are considered (Leventhal and Brooks-Gunn, 2000), with studies documenting area-based influences on outcomes such as educational attainment (Duncan, 1994), dropping out of school (Crowder and South, 2003), and test scores (Ainsworth, 2002). While the research field is younger in Europe, a small but growing base of European evidence also supports the notion that neighbourhood conditions may have effects on individual educational outcomes. As the US findings have been widely summarized and reviewed elsewhere (see above), and because of the current study’s setting, this section focuses on European research. In Scotland, Garner and Raudenbush (1991) tested for effects of neighbourhood social deprivation on the educational attainment of 2500 youth. They found neighbourhood deprivation to have a significant negative association with individuals’ overall attainment after controlling for a wide set of individual and family background characteristics. They identified the effect of neighbourhood deprivation as small, but not inconsequential. For youth of otherwise similar background and prior ability scores, the effect of neighbourhood deprivation appeared to be large enough to substantially affect their level of educational attainment and, in turn, prospects in obtaining future employment.

Neighbourhood effects on educational achievement 39 Several studies from Sweden have also shown support for neighbourhood effects on educational outcomes. In a multilevel analysis of 2400 individuals in their mid-twenties, Andersson (2004) found characteristics of individuals’ neighbourhoods during adolescence to be associated with educational attainment and occupational status (and to a lesser extent income status) in early adulthood. She found both social (e.g. income, SES, household composition) and physical (e.g. dwelling type, tenure) aspects of neighbourhoods to be related to individual outcomes. In a later study, Andersson and Subramanian (2004) found neighbourhood socioeconomic resources and instability to explain school attainment in a sample of 200,000 Swedish youth. The strongest effects came from what they refer to as ‘socio-cultural’ characteristics of the neighbourhood; namely, the share of the population with a university degree, the share of blue- collar workers, and the average level of social assistance benefits. A recent study by Brännström (2008) echoed the finding that neighbourhood conditions are associated with school achievement in Sweden. He examined secondary school achievement for around 26,000 youth, and found that while neighbourhood conditions are independently related to school outcomes, this effect is attenuated by the school context. He found the neighbourhood-level variability in achievement to drastically reduce upon inclusion of the school context in the analysis – a finding that points to the role of schools as mediators of neighbourhood effects. In Helsinki, based on a sample of 10,906 youth, Kauppinen (2007) tested whether neighbourhood conditions had an impact on (a) whether students completed secondary school, and (b) the type of secondary school diploma obtained (i.e. academically-orientated versus vocational). He found effects on the latter outcome only. The neighbourhood condition driving the effect was the ‘concentration of affluence’, a summary variable based on the share of high-income residents and residents with high educational and occupational status. Building on these research findings, Kauppinen (2008) further explored neighbourhood effects in Helsinki, incorporating youths’ school contexts into the analysis. His findings were in agreement with those of Brännström (2008) and with theoretical discussions of neighbourhood effect mechanisms: the school context is one of the pathways through which neighbourhood conditions affect educational outcomes. While the school context attenuated much of the neighbourhood effect, Kauppinen found evidence of unique neighbourhood effects as well, driven by differences in neighbourhood SES. After controlling for a range of school and background characteristics, students from higher-status areas were significantly more likely to pursue secondary school in the upper (academic) track than students in lower-status areas.

40 Chapter 2 In Britain, McCulloch and Joshi (2001) found mixed evidence for the effects of neighbourhood deprivation on young children’s cognitive test scores. They tested for effects separately on three age groups, corresponding to three different developmental phases. Associations between neighbourhood poverty and cognitive outcomes could be identified for children aged 4-5 years, to a limited extent for the 10-18 year old group, but not for the 6-9 year olds. They also tested for links between neighbourhood deprivation and children’s behaviour problems, but did not find any significant associations. Using the same data sources, McCulloch (2006) again tested for associations between children’s outcomes and their neighbourhoods, applying a different method of measuring neighbourhood characteristics. While McCulloch and Joshi (2001) used an ‘index of deprivation’ based on four aspects of neighbourhood composition, McCulloch (2006) used a set of 37 neighbourhood characteristics to create a classification of 10 neighbourhood types. He found certain neighbourhood types to significantly predict children’s cognitive and behaviour outcomes. For instance, children in neighbourhoods described as ‘deprived city areas’ had lower cognitive test scores and higher levels of behaviour problems than average, while children living in areas classified as ‘prosperous areas’ had significantly better cognitive test scores than average. McCulloch (2006) explains that the variations between his findings and those of McCulloch and Joshi (2001) are likely due to the greater informativeness of the neighbourhood classification he used, compared to the one-dimensional deprivation index used earlier. Several analyses in a variety of European settings have found significant associations between neighbourhood characteristics and educational outcomes. While the effects found, both in Europe and elsewhere, are generally small (particularly in comparison to effects from family background characteristics), a frequent claim is that they are not trivial. Living in certain environments appears to have the potential to improve young people’s chances of graduating with higher credentials in secondary school, staying in school longer, and achieving better grades – factors that are known to have implications for future life chances.

Neighbourhood effects on educational achievement 41 2.4 The present study 2.4.1 Research questions In line with the aims of this study, the following research questions were formulated: 1. How much of the variation in young people’s educational achievement exists between neighbourhoods? 2. Are youths’ neighbourhood conditions associated with their school achievement, after taking individual background characteristics into account? If so, what neighbourhood conditions contribute to these associations? 3. Do the associations between neighbourhood conditions and educational achievement differ by student SES, gender, or nativity?

2.4.2 Research context Children in the Netherlands enter secondary school around the age of 12. Dutch secondary education is a highly differentiated system, consisting of several different tracks of education, differentiated by curricula, number of years of duration, final qualifications and possible destination after secondary school; here, we denote these tracks by A, B, C, D and E1: A = pre-university education (6 years), B = senior general secondary education (5 years), C = junior general secondary education (4 years), D = pre-vocational education (4 years), E = pre-vocational education with individualized support (4 years). Students are advised by their primary schools as to the most suitable track, based on results of a standardized test taken in the final year of primary school, as well as the student’s motivation, interests, and general performance, as assessed by their teachers. While some secondary schools offer only one track, the majority are combined schools offering several different tracks and many offer all five tracks. As mentioned above, parents have the freedom to choose their child’s school – both at the primary level, and, within the limits of their child’s (advised) learning trajectory, at the secondary level. The tradition of redistributive policies in the Netherlands extends to the realm of education. In primary education, all students are assigned a weight based on their socioeconomic and ethnic background, and the total of these weights determines the level of additional funding given to the school. At the level of secondary education, schools are allocated extra funding through a ‘Local Compensatory Policy’ administered by the municipality, and schools with

1 These correspond in Dutch, respectively, to VWO, HAVO, MAVO, VBO and IVBO; today the lower three categories are merged into VMBO.

42 Chapter 2 large shares of ethnic minority pupils also receive targeted funds. Education is government-financed and free of charge, with public and private schools funded on an equal footing by the national administration. In principle, all children and youth have equal access to education, regardless of family economic resources, place of residence, or other factors; however, in reality, practices related to how parents choose schools and how schools admit students, affect the evenness of this access (Gramberg, 1998; Karsten et al., 2003, 2006; Teelken, 1999).

Data and methods 2.5 2.5.1 Data sources and sample characteristics Data analysed in this paper come from two sources. All individual data are derived from a large-scale, longitudinal cohort study of secondary school education in the Netherlands, the Voortgezet Onderwijs Cohort Leerlingen (VOCL’99). Beginning in 1999, this study follows a cohort of students from their first year of secondary school (average age 13 years, equivalent to US Grade 7) until they leave full-time education. All students who entered the first year of a sample of 126 schools belong to the cohort, totalling 19,391 students. Statistics Netherlands (CBS) constructed the sample, recruited the schools, and is responsible for (ongoing) data collection. The sample has been found to be representative of schools and students in Dutch secondary education (van Berkel, 1999). Results reported below are from analyses of just under 18,000 students. The original sample size was reduced based on the following criteria: (a) no missing values on the dependent variable (educational achievement); (b) no missing or erroneous home postcodes (used to identify students’ neighbourhoods); and (c) students’ neighbourhoods were not missing essential data. After these reductions were made, 140 students (less than 1 percent of the sample) were further excluded because their ethnic background could not be identified. These four criteria reduced the initial sample size by 1555 students (8 percent). All neighbourhood-level data come from Statistics Netherlands. While the VOCL’99 was designed to be representative of students and schools in the Netherlands, additional analyses were required to determine the representativeness of the neighbourhoods appearing in the dataset. We found the neighbourhoods in our sample to be very representative of those in the Netherlands in terms of socioeconomic characteristics (i.e. average income, share of high- and low-income residents, share of unemployment benefit recipients) and ethnic minority composition, with all values of Cohen’s effect size d lower

Neighbourhood effects on educational achievement 43 than what is considered a ‘small’ effect (range of d = 0.05-0.14) (Cohen, 1988). These neighbourhoods are somewhat more urban in character, with higher levels of population and address density (d = 0.60 and 0.65) and slightly lower shares of homeownership (d = 0.35).

2.5.2 Individual-level predictors Students’ background characteristics come from a parent questionnaire and school administrative data in the VOCL’99, and include: age, gender, nativity (0 = Dutch, 1 = non-native; a student was considered to have a non-native background if he/she or at least one parent was born abroad), family SES (based on the highest level of parental educational attainment, from 1 = primary school or less to 5 = university or postgraduate degree), and family structure (1 = married, 2 = registered partnership or living together, 3 = divorced, widowed, not married, 4 = unknown/missing). Rather than exclude the 1880 cases for which no parental education information was available, regression imputation with a random (stochastic) component was used to impute missing values, based on the relationship between relevant variables with complete cases. All other individual data were complete. The outcome variable of interest is students’ educational achievement, operationalized as the score on a standardized test taken in the first year of secondary school, during February and March 2000. The test was developed by the Dutch Institute for Educational Testing (CITO Groep) and consisted of three components: Dutch language, arithmetic, and information processing. Each component was scored out of 20, with 60 being the highest possible test score; the mean score of our sample was 36.5 (SD = 10.8; range = 5-60). The test was found to be a highly reliable measure of achievement, with a Cronbach’s alpha of 0.91 (Kuyper et al., 2003). We examined the scores of each test component for an indication of whether ethnic minority students might be disadvantaged by the language section (however, our sample includes only students enrolled in ‘regular’ secondary education; newcomers to the Netherlands with language barriers and other special needs are enrolled in transition classes). Native Dutch students scored higher, on average, on all three test components; however, this was the least so for the language component (mean scores for language, arithmetic, and information processing for Dutch followed by non-native students are, respectively, 12.7 versus 11.7, 12.5 versus 11.2, and 12.1 versus 10.5) (Kuyper et al., 2003). Table 1 shows the mean achievement scores for students in our sample, differentiated by educational class type in Year 1 (some of the class types in Year 1 consist of one track, while others are combination types, consisting of two or

44 Chapter 2 three adjacent tracks). The pattern Table 1. Mean test achievement by class type of achievement in relation to Class type n Mean SD education type is clear in the table A 1369 49.2 5.8 – those in higher tracks perform AB 4992 44.5 6.7 significantly better. The average B 516 40.7 6.8 difference between adjacent class ABC 1114 39.6 8.1 types is 3.3 points on the test, BC 2760 36.2 6.9 or 0.31 standard deviations. The C 2175 32.1 7.9 differences in this table will be useful CD 1970 28.9 7.5 when estimating the magnitude of D 1694 26.5 7.1 effects in later analyses. DE 541 21.9 7.1 E 705 19.1 6.1 2.5.3 Neighbourhood-level Total 17,836 36.5 10.8 variables Notes. A = pre-university, B = senior general Students’ home postcodes, secondary, C = junior general secondary, D recorded in the first year of = pre-vocational, E = pre-vocational with individualized support secondary school, were used to identify their neighbourhoods. The neighbourhood unit used is the ‘buurt’ – an administrative spatial subunit representing the lowest neighbourhood level in the Netherlands. In 1999, there were 10,737 of these neighbourhood units in the Netherlands, with a mean population of 1468. These neighbourhoods vary in terms of population size and surface area, but tend to be defined on the basis of natural borders, such as roads, rail- and waterways, parks, and by building styles and periods. The students in the VOCL’99 sample resided in 3085 of these neighbourhoods in 1999, representing around 29 percent of all neighbourhoods in the Netherlands. A range of data was available for these neighbourhoods through Statistics Netherlands. Guided by theory and literature, the following selection of neighbourhood variables was made: share of high-income residents, low- income residents, and unemployment benefit recipients; mean income per income earner and per resident; housing tenure (share of homeownership); mean home value; share of immigrants with a non-Western background; and neighbourhood urbanicity. In order to summarize these variables into a smaller number of constructs and to eliminate the problem of multicollinearity, a principal components analysis (PCA) was performed. We excluded the measure of non-Western immigrants from the PCA because of its highly non-normal (positively skewed) distribution and because of interpretability of neighbourhood dimensions. For this measure, a series of dummy variables was used to represent five categories of neighbourhood ethnic minority concentration, ranging from

Neighbourhood effects on educational achievement 45 (1 = 0-1 percent) to (5 = > 20 percent). ‘Urbanicity’ was also left out of the PCA because it is a categorical predictor. This predictor was constructed by Statistics Netherlands and is based on the average density of addresses in a neighbourhood, ranging from ‘very low density’ (1 = < 500 address per km²) to ‘very high density’ (5 = > 2500 addresses per km²). We use this predictor as a control, to take differences between more or less urbanized neighbourhoods into account. To say something about the wider context within which the neighbourhoods are situated, we created a set of dummy variables based on the population of the surrounding municipality, from ‘small city’ (1 = < 50,000) to ‘large city’ (3 = >150,000). The principal components analysis revealed three underlying dimensions among the variables, hereafter referred to as neighbourhood affluence, neighbourhood socioeconomic disadvantage, and housing milieu. The three factors accounted for 89 percent of the total variance. Factor scores were calculated for each neighbourhood on these three dimensions and used in subsequent analyses. Based on congruent results from an orthogonal and oblique rotation, we used the orthogonal (varimax) factors, which are uncorrelated. To ensure the robustness of the factors, we replicated the PCA with all neighbourhoods in the Netherlands and derived analogous results. The first factor, neighbourhood affluence, had high (> 0.6) loadings on the mean income per resident and per income earner, and the share of high-income residents. The highest loading on neighbourhood socioeconomic disadvantage was the share of unemployment benefit recipients, followed by the share of low-income residents. The share of homeownership and the mean home value loaded highest on the third dimension, housing milieu. Neighbourhood affluence gives an indication of the level of financial earnings in a neighbourhood, while neighbourhood socioeconomic disadvantage gives an indication of the extent of unemployment and low-income residents. These factors serve as proxies for the various processes and dynamics happening in the neighbourhood that are thought to explain why neighbourhoods are relevant for youth outcomes. These include the mechanisms previously mentioned: the kinds of role models and peer groups present, the shared attitudes, norms, and expectations (e.g. towards work and education), processes of stigmatization, social control, and so on. The housing factor can be interpreted as an indicator of the physical housing environment (i.e. the value, tenure, and to some degree, the quality of the housing stock), and also, indirectly, the social milieu. The role of homeownership has been investigated for the potential benefits it provides residents and areas – for reasons such as the lower residential turnover, which results in a more stable neighbourhood environment, as well as the attitudes and behaviours that

46 Chapter 2 might be associated with having a financial stake in an area (Rohe and Stewart, 1996; Aaronson, 2000). Homeownership has also been used as an indicator of neighbourhood stability, a factor which has been found to be predictive of the level of neighbourhood collective efficacy and social cohesion (Drukker et al., 2003; Sampson et al., 1999).

2.6 Analysis Multilevel regression analysis was used to examine the relationships between educational achievement and individual, family, and neighbourhood characteristics. A two-level model was specified, with students (level-1 units) nested within neighbourhoods (level-2 units). We began our analysis by running a null or ‘unconditional’ model. This model is estimated to determine the amount of variance in the dependent variable attributed to the individual and neighbourhood level, and to determine the initial model fit for assessing later models. The variance values from this model are used to calculate the ‘intraclass correlation coefficient’ (ICC), a measure of the proportion of the total variance that is accounted for by (observed and unobserved) factors operating at each of the two levels. After running the unconditional model, we added individual and family characteristics. We then added neighbourhood characteristics, to address the main research question about the influence of neighbourhood conditions on youth educational outcomes. In the next model, we tested cross-level interactions, to address the research question concerning differential neighbourhood effects. To test whether the addition of new parameters improves the fit of the model, the reduction in the -2*log likelihood (the ‘deviance’) was assessed. This quantity follows (asymptotically) the chi-squared distribution, with the degrees of freedom being equal to the difference in the number of parameters for the models being compared. The regression parameters in our model have the same interpretation as unstandardized regression coefficients in multiple regression; that is, they reflect the average change in the outcome variable associated with a one-unit increase in that parameter. To assess whether a specific regression coefficient is significant, it is divided by its standard error, which gives the (student’s) t test-statistic; a coefficient is significant at the 0.05 level when it is approximately twice the size of its standard error. All continuous predictors in the analysis were centred around their grand mean and a set of dummy variables was constructed for each categorical variable, with the modal category set as the reference category. This centring facilitates interpretation of the results

Neighbourhood effects on educational achievement 47 and permits the modelling of cross-level interactions without the problem of multicollinearity (see, for instance, Snijders and Bosker, 1999). Because of this centring, the intercept of all models represents the mean score for an ‘average’ student (i.e. one with mean values on all predictors). All models were estimated using MLwiN 2.0 (Rasbash et al., 2005).

2.7 Results 2.7.1 Descriptive results Table 2 displays the descriptive statistics for the individual- and neighbourhood- level variables used in the analysis, including the mean or proportion, standard deviation, and range for each variable. The average age of youth in the sample is just over 13 years, the sample is split equally by gender, almost one-fifth of the students have a non-native Dutch background, and the vast majority have parents who are married. The parental SES category with the highest frequency is ‘secondary school education’ in the higher stream, with 42 percent; 11 percent of students have parents with a primary school education or less, and 10 percent have at least one parent with a university or postgraduate degree. The neighbourhood descriptive statistics were computed at the level of the neighbourhood (n = 3085). The first three variables are the measures derived from the PCA and those following indicate the share of ethnic minorities, urbanicity, and wider setting.

2.7.2 Multilevel results Table 3 displays the results from a series of four increasingly complex models estimating youths’ educational achievement. From the null model (Model 1), the total variance is decomposed into the individual- and neighbourhood-level by calculating the ICC. In this study, nearly 28 percent (33.28 / (87.20 + 33.28)*100 = 27.6) of the unconditional variation in educational achievement is between neighbourhoods. This is considered a large ICC and indicates that while there are clearly differences in educational achievement at the level of the individual, there are also substantial differences in achievement between neighbourhoods. In Model 2, the individual-level (level-1) predictors (age, gender, nativity, SES, family status) were added. The intercept of this model represents the mean score for a Dutch male student, with married parents, and of an average age and SES. Age has a strong negative effect on achievement, with every additional year being associated with 4.94 fewer points on the achievement test. This effect reflects

48 Chapter 2 Table 2. Descriptive statistics: Individual and neighbourhood variables

Mean/ proportion SD Min. Max. Individual-level variables (n = 17,836 students) Outcome variable Educational achievement 36.47 10.85 5 60 Predictor variables Age 13.03 0.50 10.12 16.45 Gender (1=girl, 0=boy) 0.50 0.50 0 1 Nativity (1=non-native, 0=Dutch) 0.19 0.39 0 1 Family SES Primary school or less 0.11 - 0 1 Secondary education, lower stream 0.16 - 0 1 Secondary education, higher stream (reference) 0.42 - 0 1 Higher professional education 0.21 - 0 1 University or postgraduate 0.10 - 0 1 Family structure Married (reference) 0.76 - 0 1 Registered partnership or cohabitation 0.03 - 0 1 Divorced, widowed, never married 0.09 - 0 1 Missing 0.11 - 0 1 Neighbourhood-level variables (n = 3085 neighbourhoods) Predictor variables Neighbourhood affluence 0 0.84 -2.91 4.30 Neighbourhood socioeconomic disadvantage 0 0.92 -2.64 5.79 Housing milieu 0 0.86 -2.90 3.65 Ethnic minorities (% non-Western background) 0-1% 0.22 - 0 1 2-5% (reference) 0.43 - 0 1 6-10% 0.16 - 0 1 11-20% 0.10 - 0 1 > 20% 0.08 - 0 1 Neighbourhood urbanicity Not urbanized (reference) 0.24 - 0 1 Weakly urbanized 0.20 - 0 1 Urbanized 0.21 - 0 1 Strongly urbanized 0.22 - 0 1 Very strongly urbanized 0.14 - 0 1

Neighbourhood effects on educational achievement 49 Table 2. Continued

Mean/ proportion SD Min. Max. Wider setting Small city (< 50,000) (reference) 0.59 - 0 1 Medium city (50,000-150,000) 0.28 - 0 1 Large city (> 150,000) 0.13 - 0 1

the fact that older students in the sample would mainly be those who were held back in school due to poor performance or learning difficulties, while the very youngest would be those who were put ahead due to exceptional abilities. The coefficient for gender provides no evidence that boys and girls differ consistently in their achievement scores. Students with native Dutch backgrounds perform better, on average, than their peers with non-native backgrounds. Family SES has a significant and strong positive effect on achievement – the average difference associated with a move from the lowest to highest SES level is approximately 9 marks on the test (0.84 standard deviations). The coefficients for family structure indicate that compared to having married parents, having parents in an unmarried cohabitation or having an unknown or missing family status, is associated with lower test scores. This model reduces the individual-level (within-neighbourhood) variance by 20 percent and the between-neighbourhood variance by 44 percent. The significant unexplained variance remaining in the model indicates that even after controlling for students’ background characteristics, significant differences in educational achievement exist between neighbourhoods. In the next model, all neighbourhood-level predictors were added. These predictors led to a significant improvement in the model fit and explain a further 5 percent of the between-neighbourhood variance in achievement. The predictors for neighbourhood affluence, socioeconomic disadvantage, and housing milieu all have significant associations with achievement. The strongest effect of these three predictors is from neighbourhood socioeconomic disadvantage. After adjusting for individual background characteristics and other neighbourhood conditions, a one-unit increase in the level of neighbourhood socioeconomic disadvantage is associated with a decrease in achievement of 0.76 marks, or 0.06 standard deviations. Neighbourhood affluence and housing milieu are positively associated with achievement. Neighbourhoods with the greatest shares of residents with non-Western immigrant backgrounds (i.e. 11-20 percent and >20 percent) have significant and positive associations with achievement, relative to the reference category (2-5 percent). However, reduced models (not shown) reveal that these positive effects

50 Chapter 2 Table 3. Multilevel model of neighbourhood- and individual-level effects on educational achievement

Parameter Model 1 Model 2 Model 3 Model 4 Fixed effects Intercept 36.63 *** (0.14) 36.73 *** (0.17) 36.38 *** (0.36) 36.37 *** (0.36)

Level 1 (student-specific) Age -4.94 *** (0.15) -4.91 *** (0.15) -4.92 *** (0.15) Gender (1=girl, 0=boy) -0.25 ns (0.14) -0.26 ns (0.14) -0.26 ns (0.14) Nativity (1=non-native, 0=Dutch) -1.37 *** (0.20) -1.28 *** (0.20) -1.38 *** (0.20) Family SES (ref: Secondary education, higher stream) Primary school or less -3.90 *** (0.25) -3.75 *** (0.25) -3.69 *** (0.27) Secondary education, lower stream -2.43 *** (0.20) -2.36 *** (0.20) -2.24 *** (0.20) Higher professional education 2.74 *** (0.19) 2.70 *** (0.19) 2.78 *** (0.19) University or postgraduate 5.19 *** (0.25) 5.06 *** (0.26) 5.27 *** (0.26) Family structure (ref: Married) Registered partnership, cohabitation -0.76 * (0.38) -0.67 ns (0.39) -0.67 ns (0.38) Divorced, widowed, never married 0.06 ns (0.24) 0.09 ns (0.25) 0.08 ns (0.25) Missing -0.85 *** (0.23) -0.81 *** (0.23) -0.83 *** (0.23)

Level 2 (neighbourhood) Neighbourhood affluence 0.48 *** (0.13) 0.53 ** (0.18) Neighbourhood SE advantage -0.76 *** (0.13) -0.88 *** (0.17) Housing milieu 0.72 *** (0.18) 0.74 *** (0.18) Ethnic minorities (ref: 2-5%) 0-1% 0.63 ns (0.35) 0.57 ns (0.35) 6-10% 0.12 ns (0.37) 0.11 ns (0.37) 11-20% 1.58 *** (0.47) 1.52 *** (0.47) > 20% 1.53 * (0.64) 1.25 ns (0.64) Neighbourhood urbanicity (ref: Not urbanized) Weakly urbanized 0.57 ns (0.39) 0.56 ns (0.39) Urbanized -0.18 ns (0.44) -0.15 ns (0.43) Strongly urbanized 0.15 ns (0.48) 0.22 ns (0.47) Very strongly urbanized 0.76 ns (0.60) 0.79 ns (0.60)

Neighbourhood effects on educational achievement 51 Table 3. Continued

Parameter Model 1 Model 2 Model 3 Model 4 Wider setting (ref: Small city) Medium city (50,000- 150,000) -1.27 *** (0.32) -1.24 *** (0.32) Large city (> 150,000) -0.17 ns (0.52) -0.18 ns (0.52) Cross-level interaction effects Neighbourhood SE disadvantage x Nativity 0.75 *** (0.20) Neighbourhood SE disadvantage x Primary school -0.21 ns (0.25) Neighbourhood SE disadvantage x Secondary education, lower stream -0.57 ** (0.22) Neighbourhood SE disadvantage x Higher professional education 0.19 ns (0.22) Neighbourhood SE disadvantage x University, postgraduate 1.04 *** (0.32) Neighbourhood SE affluence x Primary school 0.43 ns (0.38) Neighbourhood SE affluence x Secondary education, lower stream 0.34 ns (0.29) Neighbourhood SE affluence x Higher professional education -0.46 ** (0.22) Neighbourhood SE affluence x University, postgraduate -0.17 ns (0.26)

Random parameters Within-neighbourhood variance 87.20 *** (1.00) 78.04 *** (0.89) 78.16 *** (0.90) 78.02 *** (0.89) Between-neighbourhood variance 33.28 *** (1.50) 18.76 *** (0.99) 17.02 *** (0.93) 16.80 *** (0.92) 2*log likelihood 133133.50 130461.40 130357.30 130311.90

Notes. Standard errors are in parentheses. All continuous predictors are centred around their grand mean. Ref = reference category, SE = socioeconomic, ns = not significant. *p < 0.05, **p < 0.01, and ***p < 0.001

are only apparent if differences in neighbourhood socioeconomic and housing conditions have been controlled for. In a reduced model with all individual- level predictors and only the neighbourhood ethnic minority predictors, living in the least ethnically concentrated areas is associated with a positive effect on achievement. Once neighbourhood socioeconomic and housing predictors are taken into account, this positive effect is no longer significant, implying that the effect can be explained by the more advantageous socioeconomic and housing conditions in these areas. The neighbourhood urbanicity predictors (Model 3) are not significant, but the control for the wider context suggests that living in a neighbourhood located in a medium sized city is associated with lower achievement, relative to living in a small city.

52 Chapter 2 A series of cross-level interaction terms were introduced in the fourth model to test for differential neighbourhood effects across student SES, gender, and nativity. Significant terms were retained in the model (see Model 4, cross-level interaction effects). None of the significant effects included gender, implying that the neighbourhood effects tested here do not differ for boys and girls. The significant interaction between nativity and neighbourhood socioeconomic disadvantage (coefficient 0.75) suggests that the effect of neighbourhood disadvantage on achievement is much more relevant for native Dutch students. Nearly all of the effect of neighbourhood disadvantage in the model is due to its negative impact on native students’ achievement. Figure 1 illustrates this interaction by showing the predicted achievement for both groups of students, as a function of neighbourhood disadvantage. We also explored an interaction between student nativity and the share of ethnic minorities in the neighbourhood. This produced one significant term, which was the interaction between nativity and the first (0-1 percent) category of ethnic concentration; however, due to low cell numbers (i.e. very few non-native youth live in the neighbourhoods with 0-1 percent minorities) and a lack of improvement in the model fit (χ² = 7, 4 df, p = 0.14), this interaction was left out. Cross-level interactions between student-level SES and neighbourhood disadvantage and neighbourhood affluence are also significant. While only one of the coefficients for the latter interaction reaches statistical significance, the inclusion of this interaction significantly improves the model fit (χ² = 10, 4 df,

38

Dutch 37 t Non-native n e m e v e i h c a

36 d e t c i d e r P 35

34 < 1SD Mean >1SD Neighbourhood socioeconomic disadvantage

Figure 1. Predicted achievement as a function of students’ background (Dutch/non-native)Figure 1. Pred iandcted aneighbourhoodchievement as a f usocioeconomicnction of studen tsdisadvantage.’ background (Dutch/non-native) and neighbourhood socioeconomic disadvantage.

Neighbourhood effects on educational achievement 53 p < 0.04) and reveals a coherent pattern. These two interaction effects indicate that the achievement of higher-SES students is less affected by neighbourhood socioeconomic conditions than that of lower-SES students. In fact, the outcomes of students with the highest level of SES appear to bear no relationship to level of neighbourhood socioeconomic disadvantage. The interaction between student-level SES and neighbourhood socioeconomic disadvantage is shown in Figure 2. The five levels of SES represent the lowest to highest levels of family SES in our sample. By allowing individual characteristics to moderate the impact of neighbourhood conditions, we get a more accurate idea of the magnitude of neighbourhood effects for certain subgroups. The largest neighbourhood influence in our analysis is the negative impact of neighbourhood disadvantage on the achievement of lower-SES Dutch students. For these students, the difference in achievement associated with differences in neighbourhood disadvantage could be as much as 3.3 marks on the achievement test or 0.28 standard deviations (the effect associated with a 10th to 90th percentile change in the level of neighbourhood disadvantage). A difference in achievement of this size is greater than the achievement difference between some of the class types (refer to Figure 1), more than the difference associated with a one level change in family SES, and is more than double the disadvantage associated with having a non-native background. An effect of this size is meaningful, especially when considering the differences between the class types and levels of SES. In our final model, the original within-neighbourhood variance has been reduced

ses=5 42 ses=4 ses=3 40 ses=2 ses=1 38

36

34 Predicted Achievement Predicted

32

30 < 1SD Mean > 1SD Neighbourhood socioeconomic disadvantage

Figure 2. Predicted achievement as a function of student SES and neighbourhood socioeconomic Figure 2. Predicted achievement as a function of student SES and neighbourhood disadvantage. socioeconomic disadvantage.

54 Chapter 2 by 21 percent and the between-neighbourhood variance by 50 percent. The unexplained variance remaining in the final model is significant, indicating that the model can be improved and achievement can be further explained by the inclusion of additional variables.

2.8 Discussion and conclusion This paper set out to investigate the presence and nature of neighbourhood effects on the educational outcomes of youth in the Netherlands. This was achieved by first examining the clustering of achievement at the neighbourhood level, then testing for associations between individuals’ neighbourhood conditions and their educational achievement, and finally, examining whether these associations vary across certain student-level characteristics. The ICC showed that achievement is clearly clustered at the neighbourhood level, with 28 percent of its variance associated with differences between neighbourhoods. This reveals a relatively large potential for factors associated with the neighbourhood to affect youth achievement. While much of this clustering could be explained by differences across neighbourhoods on the individual-level predictors (i.e. composition effects), we also found support for neighbourhood effects over and above composition effects. The results of the three neighbourhood indices support conventional ideas about neighbourhood socioeconomic status: disadvantaged areas are associated with lower outcomes, and affluent areas and areas with stronger housing milieus (i.e. greater levels of homeownership and home values), are associated with better outcomes. Of these three neighbourhood indicators, neighbourhood socioeconomic disadvantage had the strongest association with achievement. The share of residents receiving unemployment benefits and the share of low-income residents were the characteristics that loaded highest on, and essentially make up, this dimension. While mediating processes have not been examined in this study, conditions of unemployment and low income could be tied to mechanisms such as collective socialization, social networks, and limited opportunity structures. For example, high levels of unemployment could contribute to the perception of poor chances for future employment. Evidence of differential neighbourhood effects by student SES and nativity were found. The negative association between neighbourhood socioeconomic disadvantage and student achievement was almost entirely restricted to native Dutch students. This implies that the levels of neighbourhood unemployment

Neighbourhood effects on educational achievement 55 and low income, while relevant for the educational outcomes of native students, do not bear much weight for the outcomes of non-native youth. In a German study examining neighbourhood effects on youth delinquency, Oberwittler (2007) also found youth with an immigrant background to be less susceptible to the effects of neighbourhood disadvantage. He suggests that although native and immigrant youth may live in the same neighbourhoods, their social experiences and ‘life worlds’ may differ to some degree. In support of this, he found the way youth perceive neighbourhood social problems to differ significantly by native/ minority background. A relevant factor may also be the school conditions of non- native students in disadvantaged areas. In the Netherlands, schools with higher shares of ethnic minority and low-SES students receive extra funding for things such as more teachers and smaller class sizes; these schools may also develop practices geared towards the particular needs of their intakes. As most ethnic minority students living in disadvantaged areas would attend schools with extra support, it is possible that these schools are able to compensate for the negative effects on achievement associated with such areas. The achievement outcomes of higher-SES students were also found to be less affected by neighbourhood socioeconomic conditions than the outcomes of lower-SES students. It appears that lower-SES students make greater achievement gains, on average, from living in affluent neighbourhoods, and incur greater losses from living in disadvantaged areas, than do higher-SES students. This interaction effect might be partly explained by the role of parents as moderators of context effects. For example, higher-SES parents might be better able to divert negative neighbourhood effects or replace what is missing in their immediate surroundings, by sending their children to schools further away, or providing them with extra learning support or activities (Ellen and Turner, 1997). The degree to which high- and low-SES students and families are orientated towards their neighbourhoods might also be relevant. For example, if higher-SES families have less locally-based social networks or are able to send their children to schools or extracurricular activities that might be at a distance, it could be the case that they are less likely to be affected by their local residential conditions. These interaction effects suggest that it is the achievement outcomes of Dutch students from low-income backgrounds that are the most strongly related to neighbourhood. In accordance with most of the European findings in this field, the estimated neighbourhood effects found in our analysis were of a modest magnitude. Small differences in neighbourhood conditions are not associated with sizable consequences for achievement; however, larger differences, especially for certain subgroups, are associated with meaningful impacts. The importance of (even small) neighbourhood effects, and the relevance of such effects for policy, are

56 Chapter 2 topics that have been widely discussed (Dorling et al., 2001; Lupton, 2003). Oliver et al. (2007: 865) point out that the practical importance of small neighbourhood effects “may be far greater than their apparent empirical magnitude, partly as a result of the uncertainty about the independence of individual and neighbourhood factors”. Jackson and Mare (2007) also note that although neighbourhood effects may be small, in some cases, conditions associated with the neighbourhood may be more easily changed than certain family (and genetic) factors. The widespread prevalence of disadvantaged neighbourhoods may also mean that the overall impact of these areas on youth education is large. This paper has a number of limitations and thoughts for future research. Although our study has several strengths – including the large and nationally representative dataset, the high reliability of the outcome measure, and the test for differential neighbourhood effects – it does not address several of the important obstacles in identifying and measuring neighbourhood effects. These challenges have been well documented (Dietz, 2002; Sastry et al., 2006; Galster, 2008) and apply to this study. Most importantly, this includes the issue of endogeneity, specifically that related to ‘selection bias’ – the fact that people are not sorted randomly into neighbourhoods. Because individual factors, such as personal preferences, help to sort people into neighbourhoods, neighbourhood selection, and therefore neighbourhood conditions, should be treated as partly endogenous. In our case, we cannot be sure that the associations between neighbourhood conditions and youth achievement are the result of neighbourhood factors, or the differential selection of youth and their families into certain neighbourhoods (Sampson et al., 2002). The direction of bias resulting from endogenous sorting has been the subject of debate, however, it cannot be determined with any certainty (Dietz, 2002; Duncan and Raudenbush, 1999; Galster, 2008). Often cited as an example that would lead to an overestimation of neighbourhood effects is the case of parents who devote great effort to the welfare of their children, seeing to it that they reside in a particularly ‘good’ neighbourhood with access to good schools and peer groups. Part of the apparent statistical association between these children’s outcomes and their neighbourhood conditions may in fact be due to the unmeasured parental characteristics that led to the observed neighbourhood characteristics (Evans et al., 1992; Galster et al., 2007). A scenario illustrating the underestimation of neighbourhood effects is one in which parents who are “well-equipped to resist the effects of bad neighbourhoods choose to live in them to take advantage of the cheaper housing or perhaps shorter commuting times” (Duncan and Raudenbush, 1999). Young urban professional parents living in less well-off neighbourhoods because of their proximity to the city centre, affordable homes, and perhaps potential for ‘revitalization’, may be a case in

Neighbourhood effects on educational achievement 57 point. Here, unless parental competence is accounted for in the model, estimated effects of disadvantaged neighbourhood conditions on children’s outcomes may be biased downwards. While a number of techniques exist to try and overcome endogeneity and selection bias, as several authors have noted they have important limitations themselves (e.g. introducing a new type of bias) and have had restricted general applicability thus far (see Dietz, 2002; Galster, 2008; Sampson et al., 2002). While we could not employ any of these techniques in the current analysis, we plan to apply a differencing approach at a later stage in our research, using measures of students’ performance at two different points in time. This should offer protection from selection bias (Galster, 2008); however, due to study retention rates, the sample will be smaller and less representative than the current one. We would also like to point out that the unmeasured characteristics that would generate endogeneity in our study are those that sort people into neighbourhoods and are associated with youths’ school achievement. These are often thought to be parental motivations, ambitions, and skills and behaviour related to children and their upbringing (Evans et al., 1992; Galster et al., 2007). Research suggests, however, that some of these parenting characteristics may themselves be affected by the neighbourhood environment. Several qualitative studies have shown that parents adapt their parenting styles and employ different parenting strategies depending on features of their neighbourhood context (Furstenberg et al., 2000; Valentine, 1997; Pinkster and Droogleever Fortuijn, 2009). Such ‘adaptable’ parenting factors could include how parents seek out and access resources for their children (e.g. schools, play groups), how they react to social pressures or collective norms in the neighbourhood, and how they monitor or restrict where and with whom their children spend time (Jarrett, 1997; Valentine, 1997). While there is no doubt that non-random factors help sort families into neighbourhoods, it is also likely that after being sorted, families are still susceptible to effects from their local environment (Oliver et al., 2007). These points do not ease or refute the problem of endogeneity, rather, they highlight the complex interdependencies that exist between people and their social contexts, and the need for more substantive methods and research which accounts for them. Another potential limitation to our study is our operationalization of youths’ neighbourhoods as their addresses in the first year of secondary school. In doing this, we take a static view of youths’ residential environments and do not consider residential mobility or neighbourhood change. Other studies have, however, found point-in-time measurements of neighbourhood characteristics to be useful proxies for children’s long-run neighbourhood experiences, because the vast majority of families, if they move, move into a similar kind of neighbourhood

58 Chapter 2 (Jackson and Mare, 2007; Kunz et al., 2003). We have also relied on readily available official data to describe neighbourhood conditions. These are meant to serve as proxies for the processes that underlie neighbourhood effects, but which are difficult to measure across neighbourhoods, particularly on a national scale (Sampson et al., 2002). To the extent that these data serve as weak proxies, we may be undercutting or misestimating the role that neighbourhoods play (Brooks-Gunn et al., 1997). In conclusion, the results from this study give an indication, for the first time, of the associations between neighbourhood conditions and youth educational achievement in the Netherlands. To better understand these associations, and the mechanisms driving them, more research is needed which considers the relationships between youth, neighbourhoods, schools, and families. As there is evidence that the impact of the neighbourhood is variable, research should examine these relationships across different groups of youth. In particular, a better understanding of the relationships between family/parenting factors and the neighbourhood context, and a stronger link between school and neighbourhood research, seems essential to understanding the influence these contexts may have on youth outcomes. As Kauppinen (2008) explains, neighbourhoods play a large part in selecting students into schools, and it is in schools where some of the contextual effects occur. Research considering the ways parents may mediate or moderate neighbourhood influences on their children also has much to offer (Kohen et al., 2008; Pinderhughes et al., 2001; Pinkster and Droogleever Fortuijn, 2009). An important question for future research is why some students appear to be more or less susceptible to certain neighbourhood effects than others. Whether family or schooling factors play a role in this is an important consideration. Our results add to the evidence that, even in contexts with relatively strong social welfare and educational policies, neighbourhood effects on youths’ school outcomes may be detected. The results suggest that research which measures average neighbourhood effects across all individuals may fail to account for the real extent of effects for certain subgroups. Our study echoes the need for more research on the interconnections between individuals and families and the multiple contexts in which they inhabit. Combining neighbourhood effects research with school and family effects research is one of the ways we can further our understanding about the roles these contexts play in shaping youth educational outcomes.

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62 Chapter 2

3 School segregation and the secondary school careers of youth in the Netherlands Abstract

This paper contributes to the literature on the relationship between school segregation and youth educational outcomes in general, and educational inequalities in particular. Using data from a longitudinal Dutch cohort study, we test whether the ethnic composition (operationalized as both ethnic diversity and the share of minority ethnic students) or the socioeconomic composition of the secondary schools that youth attend have any bearing on (1) their educational achievement in the third year, and (2) their educational positions after the fourth year of secondary school. In both analyses we control for students’ prior achievement. We find that schools with large shares of minority ethnic students in the Netherlands are very ethnically diverse, and thus, school ethnic diversity and share of minority students are very highly correlated. We find a negative association between school ethnic composition and students’ third year achievement, but not their position after the fourth year. However, corroborating the results of several other studies, we find this effect to be entirely explained by differences in school socioeconomic status (SES). Importantly, we find that even when taking a set of key individual background and school characteristics into account, including youths’ prior achievement levels and socioeconomic status, several minority groups perform worse relative to the native Dutch majority. The social and ethnic composition of the schools these youth attend do not account for this educational disadvantage.

A shorter version of this chapter has been submitted for review. Co-authored by Hans Kuyper.

66 Chapter 3 3.1 Introduction Over just a few decades, international migration has dramatically changed the ethnic landscape of many European countries, in particular their large cities. These changes have left their mark on the school systems, which now serve an increasingly ethnically diverse population. Concerns about ethnic and social inequalities in educational attainment and the possible negative effects of school segregation have risen on the political and policy agenda. The segregation of students along ethnic and social lines is thought to exacerbate already existing inequalities and to be counterproductive to the goals of social inclusion and immigrant integration. The position of immigrant and minority ethnic groups in education is a cause for concern because of their disproportionately lower levels of attainment and higher rates of early school leaving and unemployment relative to non-immigrant and ethnic majority groups (Heath et al., 2008). Given the vital relationships between educational attainment and various dimensions of integration and social mobility, and the potential for educational arrangements to both perpetuate and reshape social inequalities, these issues are particularly pertinent (Bourdieu and Passeron, 1990; Crul and Vermeulen, 2003; Holdaway et al., 2009; Latten, 2005). The meaning of ethnic segregation, however, and the links between segregation and integration, are not straightforward and have been subject to over-simplification and generalizations (cf. Kalra and Kapoor, 2009; Musterd, 2003; Peach, 1996; Phillips, 2010). A recent study concluded that “the relationship between segregation and integration suffers from too much political and too little scholarly attention” (Musterd and Ostendorf, 2009: 1515). The public and political debate around segregation and integration in Europe has taken a dramatic turn in recent years. In a number of European countries there has been a marked shift towards a stronger assimilationist discourse, in which the Netherlands is a particularly poignant case (Entzinger, 2006; Vasta, 2007). Dutch immigration and naturalization policies have become stricter and the general climate around immigration and integration notably harsher. Whereas discourses of the 1980s and early 1990s tended to focus on issues of material inequality and the structural disadvantages that immigrants and their children faced, more recently increasing attention has been placed on questions of cultural differences and the supposed conflicting value systems of immigrant and native groups (de Graaf and van Zenderen, 2009; Entzinger, 2006). In the political and policy discourses of several Western European countries, minority ethnic segregated areas tend to be automatically equated with ‘problem areas’, and presumed to be inherently problematic (see Phillips, 2010, for a recent review of ethnic

School segregation and the secondary school careers of youth 67 segregation and integration discourses across Europe; see also Wacquant, 2008). The causes of segregation are often clouded in this discourse, which increasingly emphasizes the alleged unwillingness of migrants to integrate, their apparent failure “to follow normative models of social and spatial integration” (Phillips, 2010: 220), and thus, the threat they pose to social cohesion and national unity (Entzinger, 2006; Kalra and Kapoor, 2009; Thomson and Crul, 2007). Vasta (2007) argues that institutional barriers to integration are downplayed in this discourse, with one barrier being institutional features of the educational system (see also Crul and Schneider, 2009). This paper aims to shed light on the issue of school segregation by first drawing on the literature to briefly discuss the drivers of school segregation, and second, by testing the associations between school ethnic composition and students’ secondary school outcomes in the Netherlands. Educational attainment is known to be a crucial element in shaping individuals’ future life chances and a central resource for the structural integration of immigrants’ and their children. We build on past studies by conceptualizing school composition as both the average composition and the diversity of school intakes, and by examining students’ educational outcomes longitudinally, over the course of their secondary school career. We examine two kinds of educational outcomes: (1) scores on a standardized achievement test taken in Year 3 of secondary school, and (2) students’ ‘educational position’ in Year 5 of secondary school (explained further below). We are interested in whether the schools that youth of different ethnic and immigrant backgrounds attend explain any of the observed educational inequalities across these groups1.

School segregation and 3.2 educational attainment 3.2.1 Drivers of school segregation At the most general level, segregation is understood as the degree to which two or more groups who differ across certain criteria are separated from each other across spatial or organizational units (Massey and Denton, 1988). Ethnic school segregation refers to the uneven distribution of ethnic groups within a school system. This unevenness can occur both between and within schools;

1 The terms ‘immigrant background’ and ‘minority ethnic background’ are used interchangeably in this paper to refer to people who immigrated to the Netherlands and their children, as the distinction between people with an immigrant and minority ethnic background cannot be made accurately in our dataset.

68 Chapter 3 although there is a growing literature on within-school (or internal) segregation (e.g. Willms, 2010), the focus of this paper is on between-school segregation. The literature identifies the main drivers of school segregation as: (1) residential patterns and demographic trends, (2) family school choices, and (3) institutional arrangements concerning how schools acquire and sort students, particularly (a) the level of institutional differentiation in schooling (e.g. the existence and nature of academic tracking; the presence of private schools and schools with special profiles), (b) school choice policies, and (c) the level of school autonomy regarding student admission (Alegre and Ferrer, 2009; Karsten, 2010; West et al., 2004). Some of these factors can be better understood as secondary rather than primary causes of school segregation, as they themselves are the result of deeper processes (see Coldron et al., 2010, for a discussion). For example, residential segregation and school choice patterns are known to reflect, in part, the unequal resources of social, cultural and economic capital that families have available to them. An extensive body of work documents the different ways in which families mobilize their resources when choosing schools, with middle- class parents having an advantage, on average, over working-class parents (Ball, 2003; Gewirtz et al., 1995; Reay and Ball, 1997). Middle-class families typically have greater access to financial resources and ‘grapevine knowledge’ (Ball and Vincent, 1998), as well as familiarity with the cultural codes and linguistic styles dominant in the mainstream educational sector ( Ball, 2003; Gewirtz et al., 1995; Reay and Ball, 1997). A growing amount of research focuses on the third factor: how schools acquire and sort students. An increasing base of evidence demonstrates that school systems that sort students by educational trajectory (i.e. selective or stratified school systems) produce greater levels of segregation than comprehensive systems (Crul and Schneider, 2010; Jenkins et al., 2008; Schofield, 2006; Willms, 2010). In stratified school systems, students are assigned to different educational environments (e.g. ‘streams’, ‘tracks’, ‘ability groups’) based typically on their previously obtained grades, achievement test scores and teachers’ judgements. Since (previous) academic performance is correlated with socioeconomic and ethnic background in many countries, this sorting tends to reflect broader stratifications in society. Qualitative and quantitative studies from a number of countries also reveal that more market-oriented school systems tend to produce greater levels of school segregation (Alegre and Ferrer, 2009; Gewirtz et al., 1995; Johnston et al., 2007). These factors are among the reasons why there is not a one-to-one mapping between residential and educational segregation.

School segregation and the secondary school careers of youth 69 3.2.2 Effects of school segregation One of the main reasons why school segregation garners attention is the concern that it generates or reinforces educational inequalities. Concerns are also raised about the potential implications of segregation for issues of social and inter- ethnic interaction, such as the likelihood of inter-ethnic friendships, and the development of ethnic tolerance and understanding (Amin, 2002). This paper is concerned with the first issue – the potential implications of school segregation for students’ educational outcomes, and more specifically, ethnic inequalities in education. The differentiated school performance of different (social and ethnic) groups raises questions about school conditions which might be unfavourable for students’ educational development. School segregation is seen as potentially being one of these conditions. The issue of ethnic school segregation is intimately tied to social and academic (or achievement) segregation. Because of the interrelationships that commonly exist between social position, academic trajectory and immigration or ethnic background, patterns of ethnic segregation tend to overlap with those of socioeconomic and achievement segregation. For instance, in school systems that sorts students into different educational tracks (e.g. as in Germany, Austria and the Netherlands), children of non-Western migrants, many of whom have low levels of economic resources, are routinely overrepresented in ‘vocational’ tracks and underrepresented in the more ‘academic’ or pre-university tracks (Crul and Schneider, 2010; Schofield, 2010). Thus, the concern over the effects of ethnic school segregation on educational outcomes is in part due to the related patterns of segregation along socioeconomic and achievement lines. Since these three factors (ethnic, social and achievement composition) are correlated in the Netherlands – as we will show below – and since there is much overlap in the theoretical and empirical work regarding them, this section discusses the hypothesized links between school composition and students’ educational outcomes, where we consider social, ethnic and achievement composition together. School composition (i.e. the makeup of the student body) is thought to bear upon student outcomes through three broad, interrelated channels: (1) peer group processes, (2) teaching and instruction, and (3) school organization and management processes (Harker and Tymms, 2004; Schofield, 2010; Thrupp and Lupton, 2006; Thrupp et al., 2002; Willms, 2010). Peer group processes refer to interactions among peers and the influence they have on each other’s motivation, aspirations, behaviour and attitudes towards school. As Ellen et al. (2002: 185) explain, “[t]he hypothesis is that a student’s decisions about how much to study, how to behave in the classroom, and what kinds of classes to take

70 Chapter 3 are very much shaped by interactions with other students and those students’ parents, and moreover, the level of discussion and instruction in a classroom is determined by one’s peers”. Students bring different dispositions and forms of cultural, economic and social capital with them to school (e.g. linguistic styles, ways of interacting, interests and attitudes, reading habits, etc.) (Bourdieu and Passeron, 1990), which work to shape classroom social relations and climate, and in turn, students’ opportunities to learn. Reference group or social comparison processes, whereby students compare themselves on various dimensions, such as their performance at school, with their peers may also influence learning outcomes, for instance through effects on students’ academic self-concept, motivation, ethnic identification and self-esteem (Lubbers et al., 2009; Schofield, 2006). Students not only influence each other directly, but also through their effect on classroom, instructional and school processes. As Harker and Tymms (2004: 180) assert, “students ‘react’ to school structures as well as to their peers, and schools in turn ‘react’ to the composition of the student body”. In terms of teaching and instructional effects, teachers may intentionally or unintentionally adjust their instruction, expectations and pedagogical goals to certain groups or classroom compositions, which could have an impact on student learning (Hattie, 2002). It has been suggested that in more homogenous settings, teachers may be better able to develop or utilize specialized practices or skills geared towards the needs, learning styles or achievement level of the students (Karsten et al., 2006; Schofield, 2006). Language and cultural differences between teachers and students could influence the pace of instruction and detract from time spent on lessons, if, for example, teachers need to spend more time on language elaboration and explanation. The composition of the classroom has also been found to affect the amount of time devoted to issues of classroom management versus core teaching and learning tasks (Lupton, 2005). At the level of school organization and management are factors such as the recruitment and retention of teachers, the quality and experience of the teaching staff, curricula offerings and educational framework, and work and learning climate (Ellen et al., 2002; Opdenakker and van Damme, 2001). Insofar as school practices are related to the composition of the student body, as numerous qualitative studies show they are (Gewirtz, 1998; Hattie, 2002; Lupton, 2005; Oakes et al., 1992; Paulle, 2005; Thrupp, 1999), they may be pathways through which school composition has salience for student outcomes. Research finds that schools serving more disadvantaged intakes encounter more challenges with recruiting and retaining teachers (Ellen et al., 2002; Clotfelter et al., 2006; Karsten et al., 2006; Scafidi et al., 2007), attendance, behavioural and discipline

School segregation and the secondary school careers of youth 71 issues (Lupton, 2005), and in engaging the involvement and support of parents (Metz, 1990; Sui-Chu and Willms, 1996). Conversely, schools serving higher-SES youth may have some advantages concerning attracting and retaining teachers, parental support, and creating an environment conducive to running a learning and teaching organization (Thrupp et al., 2002). School-related processes in which specifically the ethnic or racial composition may be relevant include students’ language use and proficiency in the language of instruction, and ethnic tensions or ethnic-related discrimination and victimization, which could have an effect on learning (Hoxby, 2000; Verkuyten and Thijs, 2002). While most studies operationalize school composition as the average share of certain student groups, an increasing number of studies examine school ‘diversity’ or the mix of ethnic and social groups (Campbell, 2007; Dronkers, 2010; van Houtte and Stevens, 2009). These two aspects (mean composition and diversity) are conceptually distinct – for example, a school with a large share of minority ethnic students can be very ethnically diverse (students come from many ethnic groups) or more homogenous (students come from just a few ethnic groups) – but tend to be empirically related, as we will later show in the Dutch case. Diversity may be important for a number of reasons. In a school with many ethnic groups, versus just a few predominant groups, there may be more incentive for students to adopt the language of instruction, rather than to speak a common, non-instructional, language. The heterogeneity of the classroom could affect teacher’s work and classroom dynamics; for example, bridging cultural differences could prove stimulating and rewarding for students and teachers, or distracting and time-consuming. Based on their extensive fieldwork in schools, Thrupp (1999) and Lupton (2004) assert that the influence of school composition on student learning outcomes can be best understood as the cumulative impact of many small and interrelated effects tied to student, classroom, teacher and school-level processes. Referring to her study of four schools in disadvantaged areas in Britian, Lupton (2004: 6) explains: “[t]he disadvantaged contexts of the schools appeared to be influential for classroom practice and teaching resources, and for school organisation more broadly, generating numerous relatively small process effects that together contributed to school environments that were described [by school staff] as being characteristically different from those found in more advantaged settings”. Thus, student, school, teacher (and external) processes are “bound up with each other in complex ways” (Gewirtz, 1998: 455). Since the publication of the landmark Coleman report (Coleman et al., 1966) there has been an extensive amount of research on school composition and its implications for students’ learning outcomes. Making sense of the vast

72 Chapter 3 empirical findings is not an easy task. In a 2002 review of international research, Thrupp et al. (2002: 483) wrote that “[d]espite over 30 years of research into the effects of school composition or “mix,” there is remarkably little consensus over the nature and size of school compositional and peer effects”. Some studies report large associations between school composition and student outcomes and others report none. Differences in research design and methodology (e.g. the operationalization and measurement of school and student attributes; longitudinal versus cross-sectional designs), research context, and rigor are certainly at play. Nevertheless, several recent reviews and meta-analyses conclude that, on the whole, there is a good deal of evidence to support the relationship between school intake characteristics and learning opportunities, with students, on average, appearing to gain academically from attending schools with more economically and academically advantaged peers; insofar as migration or ethnic background are correlated with these attributes, students also appear to gain from attending schools with more ‘native’ peers (Karsten, 2010; Schofield, 2006, 2010; Sirin, 2005; Thrupp, 2002; van Ewijk, 2010a, 2010b).

3.3 The present study: The Dutch context 3.3.1 Immigration and ethnic minorities in the Netherlands There are four main groups of immigrants in the Netherlands: (1) postcolonial migrants from Suriname, Aruba and the Antilles, and the Moluccas (Indonesia), (2) former labour migrants (‘guest workers’) and their families, mainly from Turkey and Morocco, (3) asylum seekers from countries such as Somalia, Iraq, Iran and Afghanistan, and (4) economic migrants, who come (often temporarily) for business and employment from countries with advanced economies, such as Germany, Japan and the US. Integration policy targets the first three groups of migrants and their children (excluding those of Indonesian descent due to their higher levels of SES and longer history of migration), whom are identified in official Dutch statistics as ‘non-Western immigrants’. The Dutch state considers someone to have a non-Western immigrant background if he or she or at least one parent was born abroad in a non-Western country (second-generation immigrants are therefore included in this category). The largest waves of migration were during the postwar period, around the time of the independence of Indonesia (1949) and of Suriname (1975), and during the rapid economic expansion of the 1960s and 1970s (‘guest worker’ migration). Labour migrants were recruited to perform cheap, manual labour

School segregation and the secondary school careers of youth 73 in the Netherlands and were primarily men from rural areas with little formal education. Individuals continue to migrate to the Netherlands from these countries for reasons of employment, education and family reunification and formation. Non-Western minority groups are in a disadvantaged socioeconomic position relative to their native Dutch and Western counterparts. They have disproportionately lower levels of education and labour market participation and are overrepresented in the social security system and in lower-status sectors of the school system labour market (Entzinger, 2006). These groups are known to encounter discrimination in such fields as labour, education and the housing market (Boog et al., 2006; Pettigrew, 1998; Verkuyten, 2005). In this study, we differentiate between nine ethnic groups. Some of the categories follow those used by Statistics Netherlands and our data source (which we describe in the next section), and constitute the main immigrant groups in the Netherlands (e.g. Turkish, Moroccans, Surinamese). We merged additional groups, either because their numbers were so small, or because of their similarity in socioeconomic status and region of origin. The groups we differentiate are: native Dutch, Turkish, Moroccan, Antilleans, Surinamese, Indonesian, Asian, (other) Western immigrants, and (other) non-Western immigrants. For a small number of cases ethnic information was missing. These were grouped together in an additional category and included in the analysis to maximize sample size, but their results are not reported. In our analyses, children born in the Netherlands to non-foreign-born parents constitute the reference group (which we label as the ‘native’ group).

3.3.2 Dutch secondary education The supply of secondary schools in the Netherlands includes denominational and non-denominational schools as well as schools based on specific educational philosophies (e.g. Steiner, Montessori). All of these schools are funded on an equal footing by the national government. Geographical catchment areas do not control school admissions and students are not assigned to specific schools; rather, school choice is open, and families are free (and obliged) to choose a school. Secondary education is characterized by a high degree of differentiation in the school careers of students. Children finish primary school around the age of 12, after 8 years of education. At the end of primary education they receive a recommendation from their teachers as to the most suitable educational track (or a combination of two tracks) to follow in secondary school. This recommendation is based on their score on a standardized test taken in the final year of primary school, as well as their general performance, motivation and interests, as assessed by their teachers. There are several tracks in Dutch

74 Chapter 3 secondary education, differentiated by curricula, prestige, number of years of duration, final qualifications and possible destination after secondary school. Here, we denote these tracks by A, B, C, D and E2: A = pre-university or ‘scientific’ secondary education (6 years), B = senior general secondary education (5 years), C = junior general secondary education (4 years), D = pre-vocational education (4 years), E = pre-vocational education with individualized support (4 years). A small number of secondary schools offer only one track, the majority are combined schools offering several different tracks, and many offer all five tracks. In contrast to other stratified school systems, in the Netherlands there is a relatively high degree of flexibility to switch between school tracks (both upwards and downwards) and to take long or indirect routes through secondary education (Crul and Schneider, 2010). Well performing students can be placed in higher tracks (upward transfer) and students can also transfer to lower tracks (downward transfer), which usually takes place at the start of the following school year. It is also possible to continue in the fourth year of track B with the diploma of track C (and then be eligible for higher education), or in the fifth year of track A with the diploma of track B (and then be eligible for university). Thus, the Dutch system provides students with more possibilities for indirect routes and ‘second chances’ than, for example, the German system, which offers less upward permeability between tracks, and where indirect routes to higher education through the vocational tracks are not seen as such or used to same degree (cf. Crul and Schneider, 2010: 11; Herweijer, 2009: 135). Social class and ethnic groups are not distributed evenly across primary and secondary schools or across the different tracks in secondary education. Children of parents with low levels of education are overrepresented in the lower tracks and underrepresented in the higher tracks of secondary school. As minority ethnic students have parents with disproportionately low levels of education relative to native Dutch students, they are also found more frequently in the lower tracks and are underrepresented in the higher tracks. In the 2007/’08 school year, native Dutch students were around 2 times more likely to be in the highest two tracks (senior general education and pre-university) than students of Moroccan or Turkish origins (Herweijer, 2009). The average native Dutch secondary school student in the Netherlands has 10 percent schoolmates with a non-Western immigrant background, whereas this figure is 34 percent for immigrant students (ibid.). Based on 2006 PISA (Programme for International Student Assessment) sample data for 32 OECD countries, Alegre and Ferrer (2009) report that Dutch students in the highest SES quartile are much more segregated across secondary schools

2 These correspond in Dutch, respectively, to VWO, HAVO, MAVO, VBO and IVBO; today the lower three categories are merged into VMBO.

School segregation and the secondary school careers of youth 75 than students in the lowest SES quartile; for the former group, segregation levels in the Netherlands rank eighth highest out of the 32 countries. Also using PISA 2006 data, Schnepf (2008) reports a dissimilarity index3 of 0.55 for immigrant versus non-immigrant students across Dutch secondary schools4. Based on all secondary schools in Amsterdam in 2005, Sykes (2006) reports a dissimilarity index of 0.48 for students with non-Western immigrant backgrounds versus students with native Dutch and Western backgrounds. Using three measures of segregation (dissimilarity, isolation and concentration), Ladd et al. (2009) find high levels of ethnic segregation across primary schools in Dutch cities, both in absolute terms and relative to comparable measures for US cities5. Another noteworthy feature of Dutch education is the existence of compensatory funding policies, as part of the government’s strategy to redress educational inequalities. In addition to the right to equal funding for all (e.g. religious, public, special pedagogic) schools, redistributive funding schemes transfer proportionally more financial resources to schools that serve larger shares of students from low socioeconomic backgrounds (see Herweijer, 2009, for more on school funding in the Netherlands).

3.3.3 Research questions This study addresses the following research questions: 1. Taking individual student background characteristics and prior achievement into account, is there an association between the share of students with a non-Western immigrant background or school ethnic diversity on the one hand, and students’ academic achievement and educational position in secondary school on the other? 2. Do these associations persist after taking school socioeconomic composition or mean achievement level into account? 3. Do the schools that different minority groups attend account for any of the observed ethnic inequalities in educational outcomes?

3 Dissimilarity indices can be interpreted as the share of students from either group that would have to move schools in order to achieve an even distribution of both groups across all schools. 4 Importantly, as the authors recognize, all calculations based on PISA data (or other sampled surveys) are subject to sampling variation. The usefulness of calculating segregation indices at the national level is also questionable, as this naturally picks up on the fact that different groups are unevenly spread across the country; for example, some groups have a greater propensity to live in urban areas than others. 5 For example, in the 32 largest Dutch cities, the dissimilarity indices for ‘low-SES immigrant students’ versus ‘all others’ ranged from 0.36-0.69 (mean = 0.56).

76 Chapter 3 3.4 Data and methods 3.4.1. Data source and sample characteristics Data analysed in this paper come from a large-scale, longitudinal study in the Netherlands called the ‘Longitudinal Cohort Study in Secondary Education – Cohort 1999’ (in Dutch, the Voortgezet Onderwijs Cohort Leerlingen or VOCL’99; Kuyper et al., 2003). Beginning in 1999, this study follows a cohort of students from their first year of secondary school (average age 13 years) until they leave full-time education. A nationally representative sample of 126 schools participated in the study; all students who entered the first year of these schools in 1999 belong to the cohort, totalling 19,391 students. The sample was constructed by Statistics Netherlands, who also recruited the schools and was responsible for data collection. We used two sub-samples from this dataset for our analyses below. First, we examined students’ achievement in Year 3 of secondary school. In these models the sample size is 9967 students (51 percent of the total sample), due mainly to the lower levels of participation of schools in the second stage of testing in Year 3, which is in line with previous cohorts in the VOCL series. On average, the students in our first selection come from family settings with higher levels of SES, are more often native Dutch, and have higher levels of prior achievement than the non-selected students, with an effect size that is considered to be small (Cohen’s d = 0.3). In the second analysis we examined students’ educational position after four years of secondary school. For these models, the sample size is considerably larger, at 14,234 students (74 percent of the total sample), due to the fact that less information was missing about students’ track positions. Due to data restrictions, students who have dropped out of school cannot be accurately identified, and thus, are not included in our selections.

3.4.2 Student educational outcomes Two types of outcomes in students’ educational careers were examined: (1) students’ demonstrated achievement on a standardized test taken in Year 3 of secondary school, and (2) students’ educational position four years after beginning secondary school. In both sets of analyses we took students’ prior achievement into account, thus we were testing specifically for effects during secondary school. The advantage of including both outcomes is that because they are conceptually distinct, it permits a broader test of the potential impact of school segregation on students’ school outcomes. Year 3 achievement test scores were derived from tests developed by the Dutch Institute for Educational

School segregation and the secondary school careers of youth 77 Testing (CITO Groep), which covered subject matter taught in mathematics, text comprehension and problem solving. The test scores are a highly reliable measure of achievement, with an alpha-stratified coefficient (internal consistency reliability) of 0.91. For ease of interpretation, we standardized students’ scores on the test using the full VOCL’99 sample, resulting in an overall mean score of 50 and standard deviation of 10. The second educational outcome is based on the structure of Dutch secondary education, which is both highly tracked and flexible, as described above. We used a variant of the ‘educational ladder’, developed by Bosker et al. (1985) (see also Hustinx et al., 2009), which measures students’ educational position throughout secondary school. In our study, students’ educational position is indicated by their status at the end of the fourth year, as this is the last year that all students could be expected to be in secondary school (we subsequently refer to this outcome as ‘Year 5 position’, as it is the students’ position after completing the fourth year). In order to measure students’ Year 5 position, an interval scale ranging from 1 to 12 was constructed, encompassing all five tracks and all the potential educational positions within these tracks (Year 5 position mean = 8.14 and SD = 1.18). The scaling of the educational ladder rests on the assumption that the distances between school tracks can be considered approximately similar. In other studies, this has been shown to be a reasonable assumption (Hustinx et al., 2009). Moreover, van de Werfhorst and van Tubergen (2007) came to analogous results when they analysed school positions based on an interval scale (linear regression) and on an ordered scale (ordered logit regression) (ibid.: 444).

3.4.3 Student-level characteristics We included a number of student-level variables that prior research has shown to influence educational outcomes. Scores on a standardized test taken in Year 1 of secondary school were included as indicators of prior achievement in both sets of analyses, and students’ recommended track level was also included in the second analysis. The Year 1 test consisted of three components: Dutch language, arithmetic, and information processing. The alpha reliability of the test was 0.91 (Kuyper et al., 2003). We also standardized the test scores using the full VOCL’99 sample, resulting in an overall mean score of 50 with a standard deviation of 10. We scaled students’ track recommendations on the same interval scale described above (mean = 3.39, SD = 1.01). Other student background characteristics came from a parent questionnaire and school administrative data in the VOCL’99 dataset and included: age, gender (1 = female, 0 = male), ethnic background (the 9 groups presented above, with the native Dutch group as the reference category), family SES (based on the highest level of parental educational attainment, from

78 Chapter 3 1 = primary school or less, to 5 = university or postgraduate degree), and family structure (1 = married, 2 = registered partnership or living together, 3 = divorced, widowed, never married, 4 = unknown/missing).

3.4.4 School-level characteristics We constructed a set of school-level variables based on the student-body composition, which comprised of: the share of students with a non-Western immigrant background, the mean level of parental education, and the mean (Year 1) achievement level. Across the 126 schools, the mean share of students with a non-Western immigrant background was 0.19 (SD = 0.20), the mean school SES was 2.92 (SD = 0.50), and the mean school achievement level was 48.47 (SD = 7.00). School compositional data were based on all available cases in each school. We included a measure of ethnic diversity, which, following van Houtte and Stevens (2009), we calculated using the Herfindahl index (HI). The Herfindahl index is calculated as follows:

2 HI = -1* (Σpi ),

where pi is the proportion of each ethnic group in school i. We based ethnicity on country of origin, and included the number of students from all countries of origin in the school involved, including the native students. The HI is a continuous index that takes into account both the proportion and the number of students in an ethnic group. The index ranges between -1 and 0, with a value of -1 indicating no diversity (i.e. a homogenous ethnic composition) and a value approaching 0 indicating total diversity. In our sample of 126 schools, one school had a value of -1, indicating a homogenous ethnic composition (all students had a native Dutch background), and the highest value was -0.14. The mean level of diversity was -0.66 (SD = 0.20). We also included a set of four dummy variables indicating school denomination (public, Catholic, Protestant, other6), and three dummy variables indicated the wider school setting (small city, medium-sized city and large city).

6 Religious schools in the Netherlands emerged out of the system of pillarization, in which all sectors of social life were segmented along religious lines. This system has receded since the 1960s, although religious schools remain; nowadays, however, religious background has little to do with school admis- sions and most religious schools serve culturally and religiously heterogeneous populations.

School segregation and the secondary school careers of youth 79 3.5 Analysis 3.5.1 Estimating effects on educational outcomes The structure of the dataset is students nested within schools, and thus we used multilevel (or hierarchical) regression analysis, where students and schools form the level 1 and level 2 units respectively. We began our analysis by estimating two sets of unconditional or ‘null’ models, in which no independent variables were included (Model 1). These models partition the variance in the outcome measures into student-level and school-level components, which are used to calculate the intraclass correlation coefficient(ICC). We estimated the potential effects of school segregation in several steps. In the first step, we added only the variables for each of the 9 ethnic groups (Model 2). The estimated coefficients from this model provided a base reference point to see the extent of differences across ethnic groups in the two educational outcomes examined. In Model 3, we added a more complete set of individual and family characteristics (age, gender, family status, SES and prior achievement). The coefficients from this model can be read as an estimation of the ethnic inequalities in educational outcomes in secondary school, after taking differences in individual background characteristics, including prior educational achievement and SES, into account. In the next model, we tested for the effects of school ethnic composition and diversity (Model 4). We were interested in whether any of the observed differences in educational outcomes across ethnic groups could be attributed to school ethnic composition or diversity. In the final model (Model 5), we added school SES composition and other school characteristics to test whether the effects of school ethnic composition could be explained by school SES composition. Following this, we tested whether the mean school achievement level explained any of the observed school composition effects. We encountered two issues in our analysis. First, school ethnic composition and diversity were so highly correlated with each other (r = 0.94) that we could not include them in the same model, due to multicollinearity. Secondly, mean school SES and mean achievement were also highly correlated (r = 0.86), which made it difficult to differentiate their effects. To address these challenges, we decided to include only a single school ethnic variable (mean composition) and the mean school SES, as these correspond most closely to our research interests; in separate analyses, we also tested the effects of the omitted variables and report them below. In our final models, we tested for interaction effects between individual ethnic background and school composition, to examine whether the educational outcomes of certain ethnic groups might be more affected by school composition. All models were estimated using MLwiN, version 2.13, estimation method RIGLS (Rasbash et al., 2009).

80 Chapter 3 3.6 Results 3.6.1 Descriptives: Sample characteristics Table 1 displays key individual characteristics for all the available cases in the VOCL’99, differentiated by immigration background. In terms of mean Year 1 and Year 3 achievement, students of Indonesian and native Dutch backgrounds score the highest and students of Turkish and Moroccan origin score the lowest. Students’ track recommendation and Year 5 position (measured on an interval scale, as described above) display a similar pattern as that for achievement. There are large differences in the mean levels of parental educational attainment across the groups (measured as a categorical variable in the analyses, but collapsed into a mean score here for ease of presentation). Students with Indonesian and native Dutch backgrounds have the highest levels, while those of Turkish and Moroccan backgrounds have the lowest.

Table 1. Mean individual characteristics by ethnic group

Year 1 Year 3 Track Year 5 Group achievement achievement recommendation position Parental SES Native Dutch 51.79 50.66 3.43 8.19 3.13 Indonesian 52.33 49.95 3.51 8.24 3.26 Western 50.02 49.51 3.36 8.16 3.09 Asian 49.94 48.14 3.42 8.23 2.67 Non-Western 49.88 48.20 3.35 8.19 2.80 Surinamese 50.29 45.68 3.43 7.92 2.55 Antillean 47.27 45.96 3.13 7.86 2.68 Turkish 44.54 41.07 2.95 7.47 1.75 Moroccan 43.60 42.22 2.82 7.57 1.65 Total mean 50.00 50.00 3.40 8.15 3.02

Notes. SES = parental educational level; ‘Missing’ ethnic category omitted; N = 9967-14,234

Table 2 presents selected school characteristics for students. Concerning the average share of non-Western immigrant students, school ethnic diversity, SES and mean achievement, there is a pattern whereby Turkish, Moroccan, Antillean and Surinamese students score similarly on the one hand, as do Indonesian, native Dutch, Asian and Western students on the other, with the non-Western student category in between. Moroccan and Surinamese students attend schools with the highest share of students with a non-Western immigrant background

School segregation and the secondary school careers of youth 81 (43-44 percent), while native Dutch students attend the least ethnically diverse schools (13 percent), followed by Western and Indonesian students (18 percent). The figures for ethnic diversity are based on the Herfindahl index described above; values closer to zero indicate more diversity. Moroccan and Surinamese students attend the most ethnically diverse schools. School SES, based on the average level of parental educational attainment, is highest for Indonesian, native Dutch and Asian students, and lowest for Moroccan and Turkish students. The highest average levels of achievement, based on aggregating student achievement scores in Year 1, are in the schools attended by Asian, Indonesian, and native Dutch students. All groups of students are fairly evenly spread across schools of different denominations. Native Dutch students are more likely to live in small cities than the other groups, and Surinamese and Antillean students are the most likely to live in large cities7.

Table 2. Mean school characteristics by ethnic group, full VOCL’99 sample

Immi- Mean grant Ethnic achieve- Catho- Prote- Small Large Group share diversity SES ment lic Public stant city city N Native Dutch 0.13 -0.71 3.06 50.31 0.34 0.18 0.22 0.49 0.23 15,461 Indonesian 0.18 -0.63 3.12 50.57 0.25 0.23 0.17 0.35 0.28 359 Western 0.18 -0.63 3.01 49.58 0.18 0.18 0.21 0.39 0.24 858 Asian 0.22 -0.62 3.05 50.84 0.25 0.23 0.11 0.36 0.34 233 Non-Western 0.29 -0.55 2.93 49.26 0.28 0.18 0.20 0.29 0.38 704 Surinamese 0.44 -0.43 2.76 48.73 0.35 0.22 0.20 0.14 0.66 320 Antillean 0.41 -0.46 2.67 46.65 0.35 0.22 0.19 0.18 0.56 291 Turkish 0.40 -0.47 2.61 46.22 0.24 0.32 0.18 0.23 0.51 446 Moroccan 0.43 -0.42 2.51 43.94 0.30 0.28 0.18 0.15 0.53 478 Total mean 0.17 -0.68 3.02 50.00 0.20 0.22 0.17 0.45 0.27 19,150

Notes. SES = socioeconomic status; ‘Missing’ ethnic category omitted

Table 3 displays bivariate correlations between the school characteristics. The strong correlation between the share of immigrant students in the school and the ethnic diversity (r = 0.94) is apparent. This means that in the Netherlands, a high share of immigrant students in a school is associated with an ethnically diverse student population. This finding is in line with the results of van Houtte and

7 The categories ‘other school denomination’ and ‘medium-sized city’ are omitted from the table, but discernable from the shares in the other categories.

82 Chapter 3 Stevens (2009), who reported a correlation of 0.88 between ethnic diversity and immigrant share in Belgian schools. There is also a strong correlation between mean achievement and mean SES (r = 0.86), reflecting the relationship between socioeconomic background and educational achievement at the individual level. There are negative correlations between ethnic diversity and share of students with an immigrant background on the one hand, and mean SES and mean achievement on the other.

Table 3. Bivariate correlations between school characteristics

1 2 3 4 1. Immigrant share 1 2. Ethnic diversity 0.94 1 3. Mean SES -0.51 -0.41 1 4. Mean achievement -0.35 -0.33 0.86 1

Notes. All significant p < 0.05; N = 126; Calculated at level of the school

3.6.2 Multilevel analysis Tables 4 and 5 display the results from a series of five increasingly complex models estimating youths’ Year 3 secondary school achievement and Year 5 school position, respectively. We began the analysis by running unconditional models and calculating the ICCs (see intraclass correlations in Model 1, Tables 4 and 5). The ICC measures the proportion of variance in the outcome variable that is due to differences between groups (in this case, schools)8. It can also be interpreted as the extent to which two randomly selected individuals in the same group (i.e. school) resemble each other with respect to the outcome variable (Rasbash et al., 2009: 28). There is a substantial proportion of variance in the outcome variables associated with the school level, indicating that factors associated with the school level account for 39 percent and 41 percent of the variation in students’ achievement and educational position respectively (and, in terms of the second interpretation, that around 40 percent of the educational outcomes of two randomly selected individuals in the same school are in common). These are considered to be high ICCs and are to a large extent a reflection of the uneven distribution of students across schools in terms of their achievement level and associated characteristics. The ‘deviance’ (i.e. -2 log likelihood) in the bottom

8 The ICC is calculated as follows: 100*[school-level variance / (school-level variance + individual-level variance)] (Rasbash et al., 2009: 28).

School segregation and the secondary school careers of youth 83 odel 5 M 0.06 (0.27) 0.07 (0.34) -0.20 (0.27) -0.97 (0.61) -0.54 (0.31) -1.12 (0.63) -1.12 (0.63) -1.18 * (0.45) -1.28 * (0.52) 0.80 ** (0.29) -0.84 ** (0.42) 1.46 *** (0.32) 2.33 *** (0.37) 0.60 *** (0.01) 1.72 *** (0.14) -0.84 *** (0.15) -2.49 *** (0.59) -3.13 *** (0.70) odel 4 M 0.07 (0.26) 0.07 (0.33) -0.13 (0.26) -0.55 (0.30) -0.98 (0.61) -0.87 (0.65) -0.90 (0.61) -1.07 * (0.43) 0.78 ** (0.28) -1.08 ** (0.40) -1.40 ** (0.50) 1.45 *** (0.31) 2.35 *** (0.35) 0.60 *** (0.01) 1.70 *** (0.13) -0.85 *** (0.15) -2.48 *** (0.59) -2.93 *** (0.66) odel 3 M 0.05 (0.26) 0.05 (0.33) -0.15 (0.26) -0.55 (0.30) -1.06 (0.61) -0.96 (0.65) -0.92 (0.61) 0.79 ** (0.28) -1.08 ** (0.40) -1.11 ** (0.43) -1.42 ** (0.50) 1.46 *** (0.31) 2.34 *** (0.35) 0.60 *** (0.01) 1.70 *** (0.13) -0.86 *** (0.14) -2.57 *** (0.59) -3.11 *** (0.66) odel 2 M -0.93 ** (0.40) -1.40 ** (0.62) -5.35 *** (0.72) -3.34 *** (0.73) -4.54 *** (0.82) -2.81 *** (0.80) -2.91 *** (0.53) -2.90 *** (0.76) odel 1 M Multilevel analysis of secondary school educational achievement in 3 Year

Missing/unknown Higher professional education University or postgraduate Divorced, widowed, never married Registered partnership, cohabitation Secondary education, lower stream Secondary education, higher stream Turkish Moroccan Surinamese Antillean Non-Western Asian Western Indonesian Family structure (ref: Married) Age Family SES (ref: Primary school or less) Prior achievement 1)(Year Gender (1=girl, 0=boy) Ethnicity (ref: Native Dutch) able 4. Parameters Fixed effects Level-1 (student-specific) T

84 Chapter 3 0.127 65655.30 -3.00 (2.61) -0.49 (0.81) -0.51 (0.84) -1.00 (0.80) -0.19 (0.66) -0.21 (0.80) 2.14 *** (0.72) 6.12 *** (1.12) 42.09 *** (0.62) 0.142 65677.14 -6.01 ** (1.93) 6.86 *** (1.13) 41.56 *** (0.59) 0.154 65689.88 7.58 *** (1.22) 41.56 *** (0.59) 0.375 70138.93 38.61 *** (5.65) 64.31 *** (0.92) 0.387 70298.80 41.08 *** (5.65) 65.20 *** (0.92) Catholic Public Protestant Large city Small city School denomination (ref: Other) Mean SES Setting (ref: Medium-sized city) Share of non-Western immigrant background School-level Variance parameters Individual-level Intraclass correlation -2 x log likelihood Level-2 (school) Notes. Standard errors are in parentheses. * p < 0.05, ** p < 0.01, and *** p < 0.001; SES = socioeconomic status; ref = reference category; N = 9967

School segregation and the secondary school careers of youth 85 line of the table is used to compare the fit of the models. The difference between these values follows (asymptotically) the chi-squared distribution, with the degrees of freedom being equal to the difference in the number of parameters for the models being compared. Starting with the analysis of Year 3 achievement (Table 4), we next added students’ ethnic background, which provides an indication of the differences in educational outcomes across the ethnic groups. All immigrant groups have lower levels of achievement relative to the native Dutch reference group, with Turkish and Surinamese exhibiting the largest differences. As seen in the coefficients (Model 2), Turkish and Surinamese students respectively scored on average 5.4 points (or 0.54 standard deviations) and 4.5 points (or 0.45 standard deviations) lower on the achievement test than native Dutch students. In Model 3, the remainder of the individual predictors were added (age, gender, SES, family status, and prior achievement). As expected, these predictors explain a large degree of the ethnic differences in educational achievement, as indicated by the smaller coefficients for each ethnic variable. Most importantly, much of this difference is due to controlling for prior achievement level, as past achievement is a very strong predictor of future achievement. Once these individual predictors were taken into account, only the achievement levels of Turkish, Surinamese, Indonesian and non-Western students differed significantly from those of native Dutch students. Family SES has the expected positive association with achievement, while age has a negative association, and girls achieve higher, on average, than boys. Registered partnership or cohabitation family structures relate negatively to educational achievement relative to married family structures. The inclusion of the predictors in Model 3 led to a substantial reduction in the individual- and school-level variance (see variance parameters, at the bottom of the table), which is in large part due to the strong predictive power of prior achievement. In Model 4 the share of students with a non-Western immigrant background in the school was added, to address our first research question. This coefficient indicates a negative effect associated with the share of students with a non- Western background. This implies that after taking students’ achievement in Year 1 of secondary school into account, as well as their SES and other relevant characteristics, attending a school with a larger share of non-native students is associated negatively with achievement in Year 3. As mentioned earlier, school ethnic diversity and immigrant share are so highly correlated that they are essentially measuring the same thing, and create a problem of collinearity when entered in the model at the same time; in a separate model, we did test the effects of the ethnic diversity variable (not shown), and obtained equivalent results. Finally, in Model 5 we added school SES, as well as the other school

86 Chapter 3 characteristics (denomination and setting). School SES has a positive association with achievement, indicating the positive effect of attending schools with students from more socioeconomically advantaged backgrounds. The size of the coefficient for share of immigrant students in the school decreased by half and is no longer significant, indicating that the apparent negative effect associated with this variable is explained by the lower levels of SES found in these schools (and more specifically, school factors associated with SES). There is no effect on achievement associated with attending school in a large or small city relative to a medium-sized one, or with school denomination. When assessing the student-level predictors, we see that the effects of family SES, prior achievement, age and gender are all persistent throughout each model. After taking background characteristics, prior achievement and school characteristics into account, Turkish, Surinamese, Indonesian and non-Western students still differ significantly in their achievement level relative to the native Dutch reference group; the other groups do not differ significantly. Next, we tested whether the effect of school immigrant share might differ by ethnic group by estimating a set of cross-level interactions; we found no significant effects, and thus did not include these interactions in the model. The deviance indicates that each model in this series is an improvement over the former. Our final model explains 85 percent of the variance originally associated with the school-level (i.e. between- school variance) and 35 percent of the variance associated with the individual- level (i.e. within-school variance). Table 5 displays the models estimating students’ educational position in Year 5, following the same steps as in Table 4. In Model 2 we added students’ ethnic background, which reveals the differences in Year 5 school position across ethnicity. Turkish, Moroccan, Surinamese and Antillean students are in lower positions relative to native Dutch, while students of Indonesian, Asian, Western and non-Western backgrounds show no significant differences. The full set of individual predictors was added in the next model. Students’ achievement in Year 1 and track recommendation at the end of primary school have strong positive associations with school position in Year 5. Age has a negative association with school position, socioeconomic background has a positive association, and girls occupy higher positions, overall, than boys. The effects of family SES are clearly non-linear; the two lower groups hardly differ from the lowest group (reference category), while the two higher differ by a relatively large amount. Compared with married family structures, there is a negative effect associated with non- married structures. The inclusion of these predictors explains a large amount of the ethnic differences in educational position. Moroccan and Antillean students are no longer in a lower position relative to native Dutch, whereas Asian, Western

School segregation and the secondary school careers of youth 87 odel 5 M 0.02 (0.03) 0.10 (0.06) 0.02 (0.06) 0.09 (0.05) -0.04 (0.03) -0.02 (0.05) 0.14 ** (0.01) 0.08 ** (0.03) 0.11 ** (0.04) -0.03 ** (0.01) -0.15 ** (0.05) -0.14 ** (0.05) 0.22 *** (0.03) 0.36 *** (0.03) 0.04 *** (0.01) 0.47 *** (0.01) -0.14 *** (0.04) -0.10 *** (0.02) -0.08 *** (0.02) odel 4 M 0.02 (0.03) 0.11 (0.06) 0.02 (0.06) 0.09 (0.05) -0.04 (0.03) -0.02 (0.05) 0.11 ** (0.04) 0.08 ** (0.03) -0.03 ** (0.01) -0.15 ** (0.05) -0.13 ** (0.05) 0.22 *** (0.03) 0.37 *** (0.03) 0.48 *** (0.01) 0.14 *** (0.01) 0.04 *** (0.01) -0.14 *** (0.04) -0.10 *** (0.02) -0.08 *** (0.02) odel 3 M 0.02 (0.03) 0.02 (0.06) 0.09 (0.05) -0.04 (0.03) -0.02 (0.05) 0.11 * (0.05) 0.08 ** (0.03) -0.03 ** (0.01) -0.14 ** (0.05) -0.13 ** (0.05) 0.22 *** (0.03) 0.37 *** (0.03) 0.14 *** (0.01) 0.04 *** (0.01) 0.11 *** (0.04) -0.14 *** (0.04) -0.10 *** (0.02) -0.08 *** (0.02) -0.48 *** (0.01) odel 2 M 0.00 (0.06) 0.02 (0.04) -0.05 (0.07) -0.08 (0.05) -0.37 *** (0.07) -0.31 *** (0.08) -0.51 *** (0.06) -0.28 *** (0.06) odel 1 M Multilevel analysis of 5 Year secondary school position

Higher professional education University or postgraduate Divorced, widowed, never married Missing/unknown Secondary education, lower stream Registered partnership, cohabitation Secondary education, higher stream Indonesian Asian Non-Western Surinamese Antillean Turkish Moroccan Western Family SES (ref: Primary school or less) Family structure (ref: Married) Track recommendationTrack Age Gender (1=girl, 0=boy) Prior achievement 1)(Year Ethnicity (ref: Native Dutch) able 5. Parameters Fixed effects Level-1 (student-specific) T

88 Chapter 3 0.038 30963.09 0.23 (0.13) 0.07 (0.07) 0.06 (0.06) -0.06 (0.04) -0.06 (0.05) 0.13 ** (0.04) 0.51 *** (0.01) 0.02 *** (0.01) 0.18 *** (0.04) 0.056 30966.01 0.04 (0.11) 0.51 *** (0.01) 0.03 *** (0.01) 0.056 30963.62 0.51 *** (0.01) 0.03 *** (0.01) 0.399 39421.03 0.91 *** (0.01) 0.60 *** (0.08) 0.405 39506.42 0.91 *** (0.01) 0.62 *** (0.09) Large city Small city Public Protestant Catholic Mean SES Setting (ref: Medium-sized city) Share of non-Western immigrant background School denomination (ref: Other) Variance parameters Individual-level School-level Intraclass correlation -2 x log likelihood Level-2 (school) Notes. Standard errors are in parentheses. * p < 0.05, ** p < 0.01, and *** p < 0.001; SES = socioeconomic status; ref = reference category; N = 14,234

School segregation and the secondary school careers of youth 89 and non-Western students now occupy a more favourable position than native Dutch students of similar background characteristics. The other groups do not differ significantly from native Dutch students. These predictors lead to a very large reduction in the individual- and school-level variance, due mainly to the strong predictive power of track recommendation and prior achievement. Model 4 reveals that the share of students with a non-Western immigrant background in the school has no significant association with educational position, nor does the inclusion of this predictor result in a significant improvement to the model fit or any additional explained variance. We tested the effects of the ethnic diversity variable separately (not shown), and obtained analogous results. In Model 5, we added school SES, denomination and setting. The mean school SES has a positive association with educational position after four years, indicating the educational advantage of attending schools with higher-SES peers, even amongst students of similar social backgrounds and starting recommendations. No effects are associated with attending school in a large or small city relative to a medium-sized one. Relative to ‘other’ schools, there is a positive effect associated with Catholic schools. The inclusion of these school variables, however, does not result in a significant improvement in the model fit or additional explained variance. It appears that these school variables are of very little importance to students’ Year 5 position, at least when taking prior achievements into account. The effects of track recommendation and prior achievement, age, gender, family SES and structure are stable throughout each model. In the final model, Turkish and Surinamese students continue to occupy a lower position relative to native Dutch students, while the other ethnic groups do not diverge significantly, and students of Western and non-Western origins occupy a higher position. We also tested whether the effect of school immigrant share differs across the ethnic groups by estimating a set of cross-level interactions. As with the analyses in Table 4, we found no significant effects, and therefore left these out of the model. Our final model explains nearly all (97 percent) of the variance associated with the school-level (i.e. between-school variance) and 44 percent of the variance associated with the individual-level (i.e. within-school variance).

3.7 Discussion and conclusion In this article, we examined the potential implications of ethnic segregation in schools for two outcomes in students’ educational careers: (1) their demonstrated achievement in Year 3 of secondary school, and (2) their educational position after the fourth year of secondary school. Echoing the findings of other studies, we found the characteristics of the schools that students attend to differ widely across ethnicity. On average, native Dutch, Indonesian and Asian students

90 Chapter 3 attended schools with the most socioeconomically and academically advantaged students, as measured by mean school SES and mean achievement level. Students of Turkish and Moroccan origin stood out as attending schools with the lowest levels of SES and mean achievement. The share of students in a school with a migrant background and school ethnic diversity were very strongly correlated (r = 0.94), reflecting the high levels of ethnic diversity found in Dutch schools attended by many non-native students. This also suggests caution in using only the Herfindahl index to investigate (the effects of) ethnic heterogeneity in Dutch secondary schools, as separate from the share of minority ethnic students. With reference to our first research question – whether there is an association between the share of non-Western migrants in a school or school ethnic diversity on the one hand, and students’ achievement and educational position in secondary school on the other – we found mixed results. While we initially found a negative effect on students’ achievement associated with school ethnic composition, this effect substantially decreased and was no longer significant after taking school social composition and other school characteristics into consideration. Thus, the effect of school ethnic composition did not persist after taking school SES into account (second research question). This corroborates the findings of other studies that point to the greater importance of school socioeconomic versus ethnic composition (e.g. Dronkers and Levels, 2007). These findings suggest that school socioeconomic composition has an overall positive association with students’ achievement, even when taking individual SES and prior achievement level into account. In terms of students’ educational position, we found no evidence of an association with school immigrant share or ethnic diversity. We did find that school SES is positively associated with educational position, but this did not result in an improvement to the model fit. It appears that students’ Year 5 positions are by and large a function of their track recommendation, prior achievement levels, and other individual characteristics. The school variables considered in this study have little bearing on students’ Year 5 status, and almost no school-level variation in Year 5 position remained after taking students’ prior achievements and background characteristics into account. In both sets of analyses, individual social background has a positive effect on school outcomes, over and above prior achievements, even during the relatively short (two year) period between the achievement tests (i.e. Year 1 and Year 3 tests). This type of finding has been discussed in terms of the ‘secondary effect’ of social class on school outcomes – i.e. the effect of social class, conditional on performance (cf. van de Werfhorst and van Tubergen, 2007). Notably, individual socioeconomic status has a non-linear effect on educational position (Table 5).

School segregation and the secondary school careers of youth 91 It is particularly the highest two socioeconomic groups that gain the most in terms of school position, even when compared to students with equivalent prior achievements. Thus, among students of similar past achievements, students from the highest social classes more frequently occupy higher educational positions (i.e. are found more often in the higher tracks). Van de Werfhorst and van Tubergen (2007), in their study based on the VOCL’93, come to similar results. This could be due to factors such as differences in social group cultures and norms pertaining to desired or expected school tracks (e.g. preferences of the upper- and middle-classes for the most prestigious academic tracks) or differences in teachers’ track recommendations upon entry into secondary school. There is an ongoing debate in the Netherlands (and elsewhere) about the objectiveness of students’ track recommendations and the existence and nature of ‘over-’ and ‘under-advising’ (cf. Babeliowsky et al., 2006; Herweijer, 2009; van de Werfhorst and van Tubergen, 2007). As we included students’ prior achievement scores in our model, in addition to their track recommendations, and estimated their Year 5 positions rather than their initial track positions, it is unlikely that over- or under- advising played a large role in our analysis; nevertheless, it could be relevant for some students. The factors driving the (uneven) effects of socioeconomic background on school positions merit further investigation. We also examined whether the schools that different ethnic groups attend account for any of the observed ethnic inequalities in secondary school outcomes. Although school socioeconomic composition was relevant for students’ Year 3 achievement (and less so for Year 5 position), school characteristics did not explain the observed ethnic differences in educational outcomes. Several ethnic differentials in school outcomes remained, which were not accounted for by differences in the schools these groups attended, or by their prior achievement level or background characteristics. Thus, the results suggest that during secondary school, school socioeconomic and ethnic composition do not explain the observed ethnic differences in educational achievement or Year 5 school position. For half of the ethnic groups differentiated in this study, their lower levels of Year 3 achievement relative to the native Dutch group were entirely attributable to differences in prior educational achievement and background characteristics. This is a logical expectation – that differences in past achievements and background characteristics explain differences in later school outcomes. However, for the other four groups, differences in achievement persisted, which were not explained by the same predictors. This means that other factors, not considered in this study, are important for understanding these differences. Most of the minority ethnic groups, however, did not exhibit a lower Year 5 educational position after taking background characteristics into

92 Chapter 3 account. The ethnic differentials in educational position initially apparent (Model 2, Table 6) were largely a function of differences in prior achievement and other background characteristics. Thus, in line with Hustinx et al.’s (2009) analysis of the earlier VOCL’89 and VOCL’93 cohorts, we find students from several minority ethnic groups exhibiting a disadvantage relative to native Dutch students on their achievement scores, but not (consistently) in their educational positions. Moreover, two of the groups (the Western and non-Western category) attain higher Year 5 positions relative to native Dutch students. How should we interpret the dissimilar findings for the two outcome variables? It should be noted again that the sample sizes and timing of school outcome variables for the two sets of analyses were not the same, and neither sample includes students who dropped out or left school early. The smaller sample size for the Year 3 outcome is biased to a larger extent than the larger and more representative sample for Year 5 position; as noted above, the students in the Year 3 sample have higher socioeconomic backgrounds and levels of prior achievement and are more often native Dutch, than in the full sample. While the achievement test was designed to measure students’ academic ability in three subject areas, the Year 5 position is a broader outcome, which captures more than just demonstrated ability or achievement. Students’ general interests, motivation and longer-term educational and career plans are also likely to be important in their behaviour regarding their school positions. Primary school teachers’ recommendations also play an important role in initially assigning students to school tracks; these recommendations are not only based on achievement, but also on their impression of students’ general performance, interests and other subjective factors (e.g. Babeliowsky et al., 2006: 14). Our study has a number of caveats, strengths, and thoughts for future research. The strengths of our study include that is based on a large, longitudinal dataset, that we analyse two different types of school outcomes, that we define multiple ethnic groups (rather than a dichotomous native/non-native grouping), and that we control for prior achievements. In this way, we can more accurately comment on secondary school effects. However, it is important to note that by taking students’ prior educational achievement into account, we were specifically testing for effects that may take place during secondary school, and thus, we have not measured effects due to school segregation in former contexts (e.g. primary school). Students’ prior achievement levels will certainly capture the effects of past contexts, however, we were concerned specifically with the potential implications of segregation in secondary school. Moreover, while we find a relationship between school SES and students’ educational outcomes, we can say nothing about how (i.e. through which mechanisms) this relationship

School segregation and the secondary school careers of youth 93 might operate. As described in the literature section above, qualitative and ethnographic research in schools suggests that this effect is driven by a set of complex and interrelated processes tied to the student, school, teacher and classroom level (Gewirtz, 1998; Lupton, 2005; Oakes, 1992; Thrupp, 1999). Understanding how these processes work, particularly for different groups of students, is an important and ongoing task for research. Furthermore, selection bias is a notorious complexity in studies measuring the potential impact of contexts, as we cannot control for the fact that students are not randomly sorted and selected into schools (Duncan and Raudenbush, 1999). Research on the dynamics of school choice and admission processes demonstrates that these processes are far from neutral or arbitrary, thus it is an important challenge for research on the effects of schools to link up with research on selection and sorting into schools, to understand how these two facets of education intertwine. Our analyses have also tested for average effects across a large sample of students; we can thus comment on overall relationships, but are unable to examine more specific effects, such as those for particular groups of students. While we find empirical relationships between school composition and student outcomes, we can say little about the different dynamics happening in these environments and their potential meaning for students’ learning opportunities and educational development. Examining the everyday nature of school segregation, including both within- and between-school segregation, is an important task in this field of research. In conclusion, the results from this study suggest caution in presuming that there is a negative effect on students’ secondary school outcomes due to school ethnic composition or the share of students with immigrant backgrounds. Particularly for students’ position after the fourth year of secondary school, we find no evidence of an effect associated with school ethnic composition. In terms of achievement level, students appear to attain higher in schools with more native Dutch students, although this effect is entirely explained by the higher SES of these schools. Since patterns of school segregation along socioeconomic and ethnic lines are related, this suggests that ethnic segregation is important for students’ achievement, insofar as it is related to socioeconomic segregation. Moreover, we find that observed ethnic inequalities in school outcomes cannot be explained by the school characteristics considered in this study. Importantly, our findings suggest that several ethnic groups and students of low socioeconomic status continue to face a disadvantage in terms of their educational achievement level, which is not explained by their social background, prior achievement or schools attended.

94 Chapter 3 References

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School segregation and the secondary school careers of youth 97 4 Examining neighbourhood and school effects simultaneously: The school as a pathway of the neighbourhood effect? Abstract

Neighbourhoods and schools are two contexts in which youth spend vast amounts of their time – making friends, forming opinions and attitudes, and learning the social and academic skills that help them navigate through life. In the neighbourhood effects literature, schools are theorized to be a pathway or mechanism of the neighbourhood’s influence on children and youth. We tested this hypothesis using a longitudinal dataset of 9,897 secondary school students. We estimated school and neighbourhood effects separately, and then considered youths’ simultaneous membership in both contexts. In the latter analysis, the associations between neighbourhood characteristics and achievement were reduced to non-significance, while the associations with the school context remained strong and significant. These results point to schools as a pathway through which the influence of the neighbourhood may be transmitted, and underscore the need for better conceptualizations of the multiple and interrelated contexts that youth inhabit.

Published as: Sykes, B. and Musterd, S. (2010) ‘Examining Neighbourhood and School Effects Simultaneously: What Does the Dutch Evidence Show?’, Urban Studies, in press © 2010 Urban Studies Journal Limited1.

1 This chapter differs slightly from the published article.

100 Chapter 4 4.1 Introduction Examining neighbourhood and school processes together has been recognized as a necessary step towards better understanding the role these contexts play in the lives of young people (Jencks and Mayer, 1990; Arum, 2000; Sampson et al., 2002; Lupton, 2004). In the neighbourhood effects literature, schools are considered to be an important pathway or institutional mechanism of the neighbourhood’s influence on children and youth. As neighbourhood populations tend to inform local school populations, schools are places where young people get into contact with neighbourhood peers and their parents. Previous studies have also documented relationships between neighbourhood characteristics and the geography of education provision and consumption (Oberti, 2007; Pacione, 1997), parental school choices (Noreisch, 2007), and the internal processes of schools (Lupton, 2004; Thrupp and Lupton, 2006). Thus, the literature contends that schools are a pathway through which neighbourhood conditions may indirectly influence young people (Ellen and Turner, 1997; Leventhal and Brooks- Gunn, 2000; Kauppinen, 2008). This hypothesis has only seldom been tested, however, and the relationships between school and neighbourhood effects are still not well understood. From the standpoint of neighbourhood research on children and youth, the connections between neighbourhood and school factors are arguably among the strongest reasons why neighbourhoods matter for young people’s development and outcomes. Neighbourhoods play a role in sorting students into schools and in conditioning families’ school choices, and thus in informing the composition of local schools and their internal school processes (Lupton, 2004; Rumberger and Palardy, 2005). Research has shown that these internal school processes (e.g. peer relations, school organization and management, teacher instruction, classroom climate) and measures of school composition (normally a proxy for the former processes) are associated with a range of youth outcomes (for reviews, see Sellström and Bremberg, 2006; Thrupp et al., 2002). The few studies that have simultaneously examined the school and neighbourhood context offer some evidence for the mediation of neighbourhood effects through the school context (Pong and Hao, 2007; Brännström, 2008; Kauppinen, 2008). The current paper tests for associations between Dutch youths’ educational achievement in secondary school and features of their school and neighbourhood contexts, while taking important individual and family background attributes into account. Running separate models for schools and neighbourhoods, we first test whether features of these contexts are associated with students’ achievement. We then consider students’ simultaneous membership in

Examining neighbourhood and school effects simultaneously 101 schools and neighbourhoods, allowing us to test for the potential transfer of neighbourhood effects through the school context. The next section discusses the neighbourhood effects literature and reviews the mechanisms thought to drive neighbourhood and school effects, with a special focus on the place of schools in neighbourhood effects theory. We then present the research questions that guide our analysis, followed by a brief section in which we describe key elements of the Dutch context. A section on the current study’s methodology, data sources and analytical approach follows. Empirical results from a series of multilevel and cross-classified multilevel models are then reported, followed by a discussion of the results, caveats of our analysis, implications for future research and a conclusion.

4.2 Linking school and neighbourhood There has been a longstanding interest in the ways in which our social contexts affect us. Theories from developmental psychology describe the individual as a member of a series of interconnected and overlapping contexts, from the proximal family to the more distal city and national contexts (Bronfenbrenner, 1989). The crucial role the immediate family plays in helping to shape many child and youth outcomes is well-known. The school and neighbourhood settings, and in effect also the peer group, are the extrafamilial contexts thought to be the most salient for young people. In these settings, children and youth spend a large part of their time acquiring the formal knowledge and skills important for navigating through life, as well as developing their social competencies, attitudes and aspirations. Roots in different disciplinary traditions, as well as the complexity of disentangling and measuring the impact of contexts, has meant that the fields of ‘school effects’ and ‘neighbourhood effects’ have remained largely separate. However, scholars are increasingly joining these two fields, as well as taking other multicontextual approaches, in the recognition that the processes happening in these contexts are interrelated (Cook et al., 2002; Rankin and Quane, 2002; Brännström, 2008; Kauppinen, 2008; Kohen et al., 2008). The field of neighbourhood effects research is concerned with the role that an individual’s place of residence might play in shaping their wellbeing and life chances. The fundamental question in this field is whether the social and institutional context of a neighbourhood works in a way to disadvantage (or benefit) residents over and above what their background characteristics would predict, and how – through which processes and mechanisms – this comes about.

102 Chapter 4 As a key neighbourhood institution, schools have long been considered to be a pathway through which neighbourhood effects may be transmitted (Jencks and Mayer, 1990). In the theoretical discussions of neighbourhood effect mechanisms, schools have been hypothesized to play several roles. As a so-called institutional mechanism, schools are one of the local institutions thought to contribute to place-based effects (Sampson et al., 2002; Galster and Santiago, 2006). The notion of an institutional mechanism of a neighbourhood effect refers to the fact that neighbourhoods vary in terms of the quality, availability and access to institutional resources and services, such as libraries, childcare facilities, health services, schools and educational programmes, and this variation can bring about advantages or disadvantages for individuals. Some neighbourhoods, for example, have poor access to certain institutions, better or worse functioning schools and adequate or inadequate public service provision (Galster and Santiago, 2006; Hastings, 2009). Some areas might even be actively stigmatized or favoured by external governmental, institutional or market actors that allocate resources and determine who has access to these resources (Aalbers, 2005; Pahl, 1975). Youth living in areas not well served by certain types of educational programmes, where particular school courses or options are lacking or where schools perform relatively poorly, may be at a disadvantage to their peers with better access to these resources (Oberti, 2007). Indeed, research has documented the uneven distribution of schools across the metropolitan landscape, in terms of their specific course and programme offerings, resources, quality and absolute numbers (ibid.; Gramberg, 1998; Pacione, 1997). Oberti (2007) found school provision in the Paris metropolitan area – including the diversity and attractiveness of schooling programmes and settings – to be strongly correlated with the social profiles of different neighbourhoods and to correspond to sharp disparities. In the case of the United States, large disparities in educational resources and financing exist among districts, which clearly raises questions of equity (Kozol, 1991). Another grouping of neighbourhood effect mechanisms are social- interactional mechanisms. These mechanisms focus on the people and inter- group relations in a neighbourhood and include such processes as socialization, peer effects, role modelling, social networking, social norms and control, and collective efficacy (Jencks and Mayer, 1990). The school context is also relevant to this set of mechanisms. As a local site, the school is a place where these kinds of processes will also take place – for example, peers interacting with each other, children observing role models, parents exchanging information, and the establishment of social norms. Particularly at the primary school level, the school will serve as a meeting place for local children and their parents. With

Examining neighbourhood and school effects simultaneously 103 parallels to the field of neighbourhood effects research, school composition research considers the extent to which the composition of the student body may be relevant for various individual educational outcomes and behaviour, such as school achievement, inter-ethnic friendships and academic aspirations. Thrupp et al. (2002) explain that school composition effects were first envisioned as a hypothesis about the impact of peers on students’ motivation, aspirations, and attitudes towards school, while later work showed that characteristics of student groups can also influence school organization, curricula offerings, teacher instruction, classroom dynamics and wider management processes, which in turn have effects on student learning and achievement. Qualitative research suggests that these school, classroom, teacher and student processes interact with each other in complex ways (Gewirtz, 1998; Lupton, 2004). Despite the obvious connections between neighbourhoods and schools, few studies have examined neighbourhood and school effects together and tested for the simultaneous effects of these contexts (Leventhal and Brooks-Gunn, 2000). There are some notable exceptions. In Sweden, Brännström (2008) examined school and neighbourhood effects in a cross-classified model for around 26,000 secondary school students. He found that what originally appeared to be a large amount of between-neighbourhood variability in youths’ school outcomes was drastically reduced upon inclusion of the school context in the analysis. His results suggest that the neighbourhood’s influence is transmitted through the school context, at least for the majority of students. The work of Kauppinen (2008) in Finland also supports this finding. Upon entering school socioeconomic status (SES) into a logistic model regressing neighbourhood SES and student background characteristics on school outcomes, he found the effect of neighbourhood SES to be significantly attenuated and effectively explained by the mediating role of school SES. Pong and Hao (2007) examined neighbourhood and school conditions for a nationally representative sample of around 17,000 secondary school students in the US. They tested whether differences in neighbourhood and school conditions contributed to the achievement gaps between students of different ethnic and nativity backgrounds. Attributes of the school (i.e. SES, climate) and neighbourhood (i.e. SES, share of foreign-born and limited-English proficiency) were found to significantly predict youths’ school performance and to help explain the lower achievement of some groups. Neighbourhood effects appeared to be fully mediated by school characteristics for native youth, however for youth with an immigrant background, significant associations between school performance and neighbourhood conditions persisted after the introduction of school factors. Also in the US, Burgess et al. (2001) found the school, family, and local area characteristics experienced during youth to exhibit a significant association with individuals’ later earnings and poverty risk. As expected, the strongest factors

104 Chapter 4 were those of the family, followed by the school, and then the local area. While they did not discuss their findings in light of possible mediation effects, they demonstrated ‘extensive overlap’ in the explanatory power of the three contexts when considered together, versus separately. They argue that the impact of young people’s family contexts is exacerbated by the schools they attend and the areas they live in; however, they did not explicitly test for statistical interactions between context attributes. Ainsworth’s (2002) study of neighbourhood effects on the school outcomes of around 13,000 US tenth graders provides evidence for the existence of neighbourhood effects ­and the partial mediation of these effects through school factors. While the main notion put forth in the literature is that neighbourhood effects on youths’ school outcomes are likely to work through – that is, to be mediated by – the school context, some of the literature suggests that direct effects and interaction (moderated) effects between these two contexts may also be taking place (Burgess et al., 2001; Cook et al., 2002)1. Young people’s experiences in schools and neighbourhoods, and the impact of these two contexts, might be quite different for at least two main reasons. First, these two contexts will clearly not be geographically embedded for all students; that is, they may be in entirely different locations and comprise entirely different populations and social environments. And second, functional differences between the neighbourhood and school context, as well as differences in individuals’ extent and frequency of exposure, the existence of specific policies and interventions, and so on, will mean that even if these two contexts do share some geographical and population overlap, different processes (or the same processes of different intensities) would nonetheless be taking place in them (Szulkin and Jonsson, 2007). Certainly, for different types of outcomes (e.g. behavioural, educational, health), the nature of and potential relationship between neighbourhood and school effects is expected to vary (Oberwittler, 2007). Moreover, differences in school choice and admission policies, school provision, and urban scale, will also likely result in variation in the relationships between schools and neighbourhoods across different policy frameworks and settings. If effects associated with the school and neighbourhood are taking place, it is also possible that one of these contexts could buffer (or reinforce) the negative or positive processes of the other. This idea is in part what motivates parents in weak neighbourhood environments to send their children to schools outside of their area (Karsten et al., 2003). While the notion of one context buffering or moderating the effects of another has been put forth by several authors

1 See Baron and Kenney (1986) for a classic discussion of mediation, moderation and direct effects, and Plybon and Kliewer (2001) for an example in the field of neighbourhood effects.

Examining neighbourhood and school effects simultaneously 105 (Burgess et al., 2001; Hanushek et al., 2003; Oberwittler, 2007; Brännström, 2008), only a few have touched upon it in empirical studies. Cook et al. (2002) tested whether certain constellations of school, neighbourhood, peer, and family context might work in an interactive rather than additive fashion in predicting youths’ longitudinal success. As they explain, “[t]he hope was to identify combinations of contexts that especially protect young people by more than additively countervailing against any negative contextual forces in their lives” (Cook et al., 2002: 1286). They found no evidence to support this, however, as the measures of context quality that they used appeared to work additively. While they tested for interaction effects between key features of the different contexts, they did not explore whether the influence of any one context was mediated through another context – which is probable, given the correlation and overlap among the different context attributes. The findings discussed above shed light on neighbourhood–school links and the effects that these contexts may have on young people’s educational outcomes. After studying the literature, several questions emerge. There is a longstanding notion in the neighbourhood effects literature that neighbourhood conditions might influence young people’s outcomes by way of the school; this suggests the mediation of neighbourhood effects through the school context. Some of the literature also suggests that these contexts may have important direct or interaction effects. In this paper we explore whether the neighbourhood plays a role in predicting young people’s school outcomes, to what degree this role is mediated (or confounded) by the school context or direct, and whether there are interactions between neighbourhood and school characteristics.

4.3 The present study This paper focuses on the associations between characteristics of youths’ school and neighbourhood contexts and their academic achievement in secondary school. On the basis of the literature, we formulated the following research questions: 1. Are neighbourhood and school characteristics associated with youths’ educational achievement after controlling for a set of individual and family background variables? 2. Is there evidence that the school context mediates the neighbourhood’s association with youth achievement? Are there indications of direct neighbourhood effects as well? 3. Can interaction effects between these two contexts be identified?

106 Chapter 4 Several studies have indicated key differences in context effects on youth with migration or ethnic minority backgrounds on the one hand, and ‘native’ or ethnic majority youth on the other (Pong and Hao, 2007; Brännström, 2008); therefore, we will pay attention to the comparison of native Dutch and ethnic minority students in each of the three research questions. Based on previous findings of non-linear context effects (Galster et al., 2007), we will also explore the potential non-linearity of neighbourhood and school effects.

4.3.1 The Dutch context Most children in the Netherlands begin primary school at the age of four and transition to secondary education at the age of 12. Dutch secondary education is a selective system differentiated by five main academic tracks: A = pre-university education (6 years), B = senior general secondary education (5 years), C = junior general secondary education (4 years), D = pre-vocational education (4 years), E = pre-vocational education with individualized support (4 years). Students are advised by their primary schools as to the most suitable kind of secondary education, based mainly on results of a standardized test taken in the final year of primary school, as well as their general performance and interests, as assessed by their teachers. While some secondary schools offer only one track, the majority are combined schools offering several different tracks and many offer all five. The Dutch education system is characterized by a long history of open school choice and the absence of formal school catchment areas. Parents are free (and obliged) to choose their children’s school, both at the primary and secondary level. Education is free of charge and all schools (e.g. public, denominational, special pedagogical) are funded on an equal footing by the national administration. It is the government’s objective to provide equal school opportunities to all students. In an effort to re-balance the potential negative effects of social background in primary education, all students are assigned a weight based on their socioeconomic (and until recently, migration) background, and the total of these weights determines the level of additional funding given to the school. Similar types of mechanisms operate at the level of secondary education, with extra funds allocated to schools with larger shares of socioeconomically disadvantaged pupils (see Herweijer, 2009, for more on school funding in the Netherlands). While all children and youth have equal access to education in principle, in reality, there are differences across schools in terms of quality and the type of atmosphere they offer, as well as the way they admit students. School choice and admission are not neutral processes and some families clearly have an advantage over others in securing entry into particular schools (Gramberg, 1998; Karsten et al., 2003, 2006).

Examining neighbourhood and school effects simultaneously 107 4.4 Data and methods Data analysed in this paper come from a large-scale study in the Netherlands called the ‘Longitudinal Cohort Study in Secondary Education – Cohort 1999’ (in Dutch the Voortgezet Onderwijs Cohort Leerlingen, or VOCL’99). Beginning in 1999, this study follows a cohort of students from their first year of secondary school (average age 13 years old) until they leave full-time education. From a random sample of 246 schools, 126 schools participated in the study. All students who entered the first year of these schools in 1999 belong to the cohort, totalling 19,391 students. The sample was constructed by Statistics Netherlands, who also recruited the schools and was responsible for data collection. The VOCL’99 dataset was matched using individuals’ postcodes to neighbourhood identifiers, which were then matched to neighbourhood characteristics published by Statistics Netherlands. The full VOCL’99 sample has been found to be representative of students and schools in Dutch secondary education (van Berkel, 1999), as well as neighbourhoods in the Netherlands (Sykes and Kuyper, 2009). We use a much-reduced version of this dataset due to the criteria for our analysis, which are as follows: (a) no missing values on the dependent variable (Year 3 achievement); (b) no missing values on the control variable for prior achievement (entry test achievement); and (c) no missing values on essential background variables. These three criteria reduce the sample size to 9897 students; this is a reduction of 49 percent and is largely due to the 9016 students for whom there were no Year 3 achievement scores and the additional 408 students missing scores on the entry test. The missing values on the Year 3 test were mainly due to the non-participation of certain schools in the second stage of testing. The extent of non-participation is in line with previous cohorts in the VOCL series and largely reflects the lower levels of participation on the part of schools offering the lowest (i.e. vocational) tracks of education. Due to the over-representation of ethnic minority students and lower-SES students in the vocational education tracks, this non-participation results in our selection of students containing comparatively less ethnic minorities (12 percent versus 17 percent in the full sample), comparatively more students with higher socioeconomic backgrounds, and comparatively more students living in neighbourhoods and attending schools with higher levels of SES and smaller shares of ethnic minorities. On average, the students in our selection come from more economically advantaged family, neighbourhood and school settings, and have higher levels of prior achievement than the non-selected students, with an effect size that is considered to be small (Cohen’s d = 0.3). Naturally, students who have dropped out of school are not included in our selection. The omission of dropouts and the

108 Chapter 4 relatively more economically advantaged circumstances of our sample is likely to result in a more stringent test for context effects, as past empirical findings have suggested that dropping out may be influenced by school and neighbourhood conditions (Crowder and South, 2003) and that the achievement levels of youth from higher socioeconomic backgrounds are less affected by neighbourhood and school attributes (Sykes and Kuyper, 2009).

4.4.1 Individual variables Students’ background characteristics came from a parent questionnaire and school administrative data in the VOCL’99 and include: age, gender, ethnic minority background (0 = native Dutch, 1 = ethnic minority group2), family SES (based on the highest level of parental educational attainment, from 1 = primary school or less, to 5 = university or postgraduate degree), family structure (1 = married, 2 = registered partnership or living together, 3 = divorced, widowed, never married, 4 = unknown/missing), and prior achievement. Parental income or occupational data could not be used as indicators of SES due to large amounts of missing values; however, educational attainment has been found to be a good proxy for SES in the Dutch context (van Berkel-van Schaik and Tax, 1990), and research based on the previous (1993) cohort of the VOCL found parental occupational data to have no additional explanatory power in predicting youth achievement once parental educational status was considered (Veenstra and Kuyper, 2004). For the 603 cases missing parental educational information, regression imputation with a random (stochastic) component was used to impute missing values based on the relationship between relevant variables with complete cases. All other individual data were complete. The outcome variable of interest is students’ achievement in secondary school, operationalized as their scores on a standardized test taken in Year 3 of secondary school that consisted of three components: text comprehension, mathematics and problem solving. The test is a highly reliable measure of achievement, with a Cronbach’s alpha-stratified (internal consistency reliability) of 0.91. For the mathematics section, two versions were administered – one to students in the lowest two (vocational) tracks and another one to students in the highest three tracks; these two versions were later equated (see Zijsling et al., 2005, for more details). In some models, scores from a standardized entry test taken in the first year of secondary school are used to control for prior achievement. The entry test also consisted of three components, namely, Dutch language, arithmetic,

2 A student was considered to have an ethnic minority background if he/she or at least one parent was born abroad in a non-Western country, as defined by Statistics Netherlands.

Examining neighbourhood and school effects simultaneously 109 and information processing; this test was designed to be applicable to all tracks. The entry test also has a Cronbach’s alpha reliability of 0.91 (Kuyper et al., 2003). Both tests were developed by the Dutch Institute for Educational Testing (CITO Groep). For ease of interpretation and comparison, we standardized students’ scores on each test using the full VOCL’99 sample, resulting in overall mean scores of 50 and standard deviations of 10.

4.4.2 Neighbourhood variables In this study we operationalize ‘neighbourhood’ as the lowest administrative spatial subunit in the Netherlands, the ‘buurt’. These areas vary in terms of number of inhabitants and surface area, and tend to reflect natural borders, such as roads, rail- and waterways, parks and building styles and periods. Nationwide, there were 10,737 of these neighbourhoods in 1999, with a mean population of 1468. Students in our sample represent 2248 (21 percent) of these neighbourhoods. The characteristics that we consider for these neighbourhoods are: concentration of ethnic minorities (defined by Statistics Netherlands as the share of non-Western migrants; due to a negative skew this predictor was divided into quintiles); high-SES (operationalized as the share of high-income residents); and low-SES (operationalized as the share of residents receiving unemployment benefits). In a principal component analysis of six neighbourhood socioeconomic indicators (i.e. the share of high-income residents, low-income residents, unemployment benefit recipients, mean income per income earner and per resident, mean home value), ‘high-income’ and ‘unemployment’ emerged as the most important indicators of the constructs of neighbourhood ‘affluence’ and ‘disadvantage’ (which we term high- and low-SES, respectively). We estimated models with the two extracted principal components, as well as with z-score summary scales of the high- and low-SES indicators, and came to equivalent results as when using ‘high-income’ and ‘unemployment’; thus, to assist interpretation and comparison with the school SES variables, we use these two variables to represent neighbourhood high- and low-SES. Including these two variables in our model naturally reduces the problem of multicollinearity, which would occur if we entered all the (highly correlated) neighbourhood socioeconomic indicators into the model at once. We take the wider context within which the neighbourhoods are situated into account with a set of dummy variables based on the population of the surrounding municipality, from ‘small city’ (1 = < 50,000) to ‘large city’ (3 = >100,000).

110 Chapter 4 4.4.3 School variables Schools are the second level-2 unit in this study. Students in our sample attend 105 schools. We conceptualize the ‘school’ level as being the full first year cohort at a given school, due to the sampling design of the VOCL’99 (i.e. all first year classes in a school were sampled). Accordingly, all school compositional variables are made by aggregating the individual-level characteristics of these students. The following school characteristics are included: concentration of ethnic minorities (defined as the share of students with non-Western migrant backgrounds, divided into quintiles); low-SES and high-SES (two variables, defined as the share of students at the bottom and top ends of the SES categories, which are represented by parental education levels of primary or lower-secondary school, and university or postgraduate degree, respectively); and school denomination (five categories: public, Catholic, Protestant, Reformation, other3). Since some schools offer several different tracks, and others only one or two adjacent tracks, we control for this with the variable school type (0= single track, 1= multiple track). Table 1 shows the correlations between all neighbourhood- and school-level variables, calculated at the level of the student and differentiated by native/ ethnic minority status. First looking at the within-neighbourhood and school correlations, we can see that low-SES and ethnic minority concentration are clearly related in both these contexts; these correlations are strongest for ethnic minority youth (r = 0.63 for neighbourhoods and 0.60 for schools). Between neighbourhoods and schools, the SES measures have medium-sized correlations. Ethnic minority concentration appears to be much more coupled at the school and neighbourhood level for ethnic minority youth (r = 0.62) than for natives (r = 0.39). These correlations indicate that youths’ school and neighbourhood compositions are moderately to highly correlated. In addition, there is a stronger overlap between the ethnic milieus of youths’ schools and neighbourhoods than the SES milieus, and both of these dimensions are more strongly related for ethnic minority youth than for natives.

3 Religious schools in the Netherlands emerged out of the system of pillarization, in which all sectors of social life became segmented along religious lines. However, since the 1960s, this system has receded in the face of the growing secularization of society. Nowadays, most religious schools are culturally and religiously heterogeneous and schools’ religious backgrounds have little effect on ad- missions policies and families’ school choices.

Examining neighbourhood and school effects simultaneously 111 Table 1. Bivariate correlations between neighbourhood and school characteristics

1 2 3 4 5 Native Dutch students 1. Neighbourhood ethnic minorities (%) 1 2. Neighbourhood low-SES 0.40 1 3. Neighbourhood high-SES -0.26 -0.58 1 4. School ethnic minorities (%) 0.39 0.11 0.05 1 5. School low-SES 0.12 0.28 -0.32 0.34 1 6. School high-SES 0.08 -0.13 0.31 0.08 -0.66 Ethnic minority students 1. Neighbourhood ethnic minorities (%) 1 2. Neighbourhood low-SES 0.63 1 3. Neighbourhood high-SES -0.47 -0.71 1 4. School ethnic minorities (%) 0.62 0.40 -0.28 1 5. School low-SES 0.31 0.39 -0.43 0.60 1 6. School high-SES -0.08 -0.20 0.32 -0.25 -0.70

Notes. All significant p < 0.05. N = Native Dutch 8720, ethnic minority 1177; calculated the level of the student.

4.5 Analysis The structure of our dataset is students nested within neighbourhoods and schools. Since not all students in a given neighbourhood attend the same school, and not all students from a given school live in the same neighbourhood, this dataset is said to have a ‘cross-classified’ structure and is best modelled using cross- classified multilevel analysis (Goldstein, 2003). Cross-classified models recognize the simultaneous membership of level-1 units (here, students) in multiple higher- level but non-nested units (here, schools and neighbourhoods). These models estimate the influence of each context while controlling for the respective other context, making it a well-suited strategy to deal with the case of individuals embedded in and potentially influenced by schools and neighbourhoods. We began our analysis by estimating a set of unconditional or ‘empty’ models. These models identify the amount of variance in the dependent variable that is attributed to each of the levels and are used for assessing the fit of later models. From the variance values, the ‘intraclass correlation coefficient’ (ICC) can be calculated, which measures the proportion of the total variance that is accounted for by (observed and unobserved) factors operating at each of the levels and gives a rough indication of the importance of each level. After running

112 Chapter 4 the unconditional models, we ran separate 2-level neighbourhood and school models, adding individual and family characteristics and context attributes. We then combined the neighbourhood and school models into a cross-classified model, allowing us to address our main research question. We ran our first set of models without controlling for students’ prior achievement, to get a first indication of broader contextual associations and potential effects. We did this for two main reasons. The first was because of the short time span between the measures of entry test and Year 3 achievement, which may leave little room for measurable effects to take place and result in too conservative of a test for context effects (Rumberger and Palardy, 2005). Prior achievement is naturally a powerful predictor of later achievement; in our sample, students’ scores on the two tests are highly correlated (r = 0.70). Because prior achievement will reflect the cumulative effects of an individual’s previous social history and past contexts, by including it in the model we run the risk of ‘over-controlling’, that is, controlling for some of the influence of past neighbourhood and school (as well as peer and family) conditions (Sampson et al., 2002). Neighbourhood effects theory stresses the cumulative impact of one’s residential environments (Duncan and Raudenbush, 1999; Galster et al., 2007), therefore, by controlling for prior achievement, we are also controlling for some of the context effects experienced up until that point, which could undercut the potential importance of long-term neighbourhood influences and cloud our understanding of the full impact of these settings (cf. Sampson et al., 2002). Secondly, our main aim is to test for the potential mediation of neighbourhood effects through the school context, as opposed to assessing school effectiveness or the value-added of a specific programme or practice during secondary school. Thus, we have chosen to follow the strategy of Kauppinen (2008), and to compare models both with and without the control for prior achievement. However, given the short amount of time between the two tests and their high correlation, we expect only modest context effects on achievement in the models with prior achievement (Blau et al., 2001). In our final models, we tested for interaction effects between neighbourhood and school characteristics. This is based on the premise that the effects of one context might vary as a function of the other, for example, due to attributes of one context buffering the impact of the other context. All models were estimated using MLwiN, version 2.13 (Rasbash et al., 2009).

4.5.1 Analytical and methodological challenges A number of important theoretical and methodological issues arise when trying to conceptualize and measure the influences that social contexts have

Examining neighbourhood and school effects simultaneously 113 on individual outcomes. While multilevel modelling and related approaches are useful tools for addressing the question of context effects and estimating associations, they are not without shortcomings. In these models, each level of the model is treated as separate (here, the individual and family, school, and neighbourhood), while in reality we know these to be interrelated spheres with reciprocal relationships (Diez Roux, 2004). Selection bias and endogeneity are also well-known challenges to estimating context effects, as individuals are not sorted randomly into their schools, neighbourhoods, friendships groups, etc., and thus, attributes of these contexts should not be treated as completely exogenous to them (see, for example, Dietz, 2002; Galster, 2008). Examining both school and neighbourhood effects together poses a substantial challenge, as it involves the simultaneous non-random assignment of individuals to more than one context, implying multiple sources of potential selection bias. Families come to reside in neighbourhoods through non-random processes, and clearly, schools do not acquire students at random. Thus, this modelling strategy is useful for gauging the relative importance of different contexts for youth outcomes and their relations; at the same time, however, we have to keep in mind that processes in each context (e.g. home, neighbourhood, school) are (causally) intertwined (cf. Pacione, 1997). While there are several strategies that attempt to take selection bias into account, we are unable to employ a first difference equation (e.g. Galster et al., 2008) due to limitations of our dataset (i.e. many of the variables that would be needed are available for only one point in time), and given the multiple sources of selection bias and multiple contexts considered, finding good instrumental variables proves unfeasible. However, taking a cue from school effectiveness research (Goldstein, 1997; Raudenbush and Willms, 1995), we argue that controlling for prior achievement – in addition to individual and family background characteristics – is likely to guard against at least some selection bias. Including prior achievement in our models is expected to offer some protection from selection bias because this variable will capture much of the past social history of individuals, including omitted background variables and other unmeasured factors that might have helped sort them into their current neighbourhoods and schools. This is by no means an ideal control for selection bias – for example, some of these ‘unmeasured factors’ will undoubtedly continue to have an effect after youth have been sorted. However, our main aim is to test for the potential mediation of neighbourhood effects through the school context. While mediation certainly implies causation, we believe that an analysis of the data currently available, which allows us to examine school and neighbourhood contexts together and their simultaneous associations with youth outcomes, will provide

114 Chapter 4 insights into the potential links between school and neighbourhood effects and produce results that may be highly suggestive of mediation. Nevertheless, as Diez Roux (2004: 1964) remarks:

Although using the most appropriate model for the research question at hand is of course important, ultimately models are simply tools that help us describe the data. Inferring causality is a much more complicated process and requires more than statistical models.

We will come back to the issue of selection bias in the final section.

4.6 Results 4.6.1 Descriptives: Sample characteristics Table 2 describes the characteristics of our sample, differentiated by native/ethnic minority background. For both groups of students there are slightly more girls than boys. The more socioeconomically advantaged circumstances of native Dutch students, on average, are apparent. Native Dutch youths’ parents have higher average levels of educational attainment, the largest difference being between those with a primary school education or less (5 percent for natives versus 25 percent for ethnic minority students). Native Dutch students’ families appear to be more often intact (i.e. higher levels of marriage and lower levels of divorce); however, ethnic minority students have a greater share of missing values on this predictor. Ethnic minorities are more likely to live in larger cities, and attend schools and live in neighbourhoods with higher concentrations of minorities and lower levels of SES. Both groups of students are spread across all of the school types, with Catholic, Protestant, and public schools being the most common. The majority of both groups attend schools offering multiple tracks.

4.6.2 Multilevel and cross-classified analysis We began the analysis by running unconditional models and calculating the ICCs, in order to see where the variation in student achievement lies. All models were run separately for native Dutch and ethnic minorities. Model 1 in Table 3 is a 2-level model with students nested in neighbourhoods. For both native and ethnic minority youth, there is a substantial proportion of variance in achievement associated with the neighbourhood level, as indicated by the ICCs, implying that

Examining neighbourhood and school effects simultaneously 115 Table 2. Descriptives: Individual, school and neighbourhood characteristics

Native Dutch Ethnic minority Variable Mean SD Mean SD Individual characteristics Year 3 achievement (outcome variable) 50.63 (9.84) 46.39 (10.41) Year 1 achievement 51.73 (9.71) 48.49 (10.11) Age 12.97 (0.45) 13.15 (0.58) Gender (girl) 0.52 0.53 Family SES Primary school or less 0.05 0.25 Secondary education, lower stream 0.15 0.20 Secondary education, higher stream 0.47 0.31 Married 0.85 0.65 Registered partnership or cohabitation 0.03 0.04 Divorced, widowed, never married 0.07 0.12

Missing/unknown 0.06 0.19 School characteristics Low-SES (%) 0.24 (0.14) 0.31 (0.20) High-SES (%) 0.09 (0.16) 0.09 (0.18) Ethnic minority concentration Q1 (least) 0.26 0.05 Q2 0.27 0.15 Q3 0.24 0.27 Q4 0.17 0.28 Q5 (most) 0.06 0.26

(observed and unobserved) factors associated with the neighbourhood level account for 28 percent and 40 percent of the variation in students’ achievement, respectively (see ICC in Model 1, Table 3) (Goldstein, 2003). These are considered to be very high ICCs and will be to a large extent explained by the uneven distribution of students across neighbourhoods in terms of achievement level and associated characteristics. In Model 2, schools are the level 2-units. In these models, a greater proportion of variance is associated with the school level (i.e. 38 percent for natives and 42 percent for ethnic minority students). While this indicates a large potential for school characteristics to affect achievement, much of this variation will also be explained by the uneven distribution of students

116 Chapter 4 Table 2. Continued

Native Dutch Ethnic minority Variable Mean SD Mean SD School denomination Public 0.18 0.32 Catholic 0.39 0.36 Protestant 0.21 0.20 Other 0.09 0.11 Reformation 0.13 0.02 School type Multiple track 0.80 0.69 Single track 0.20 0.31 Neighbourhood characteristics Low-SES (%) 0.16 (0.07) 0.21 (0.08) High-SES (%) 0.22 (0.08) 0.19 (0.09) Ethnic minority concentration Q1 (least) 0.05 0.01 Q2 0.40 0.16 Q3 0.25 0.17 Q4 0.17 0.22 Q5 (most) 0.12 0.44 Wider context Small city (< 50,000) 0.66 0.33 Medium-sized city (50,000-100,000) 0.21 0.35 Large city (> 100,000) 0.13 0.32

Notes. N = Native Dutch 8720, ethnic minority 1177; SES = socioeconomic status

across schools in terms of achievement level and associated characteristics. Cross-classified models are specified in Model 3. In these models we see a drastic reduction in the proportion of variance at the neighbourhood level, while the school-level variance remains large. This provides the first indication that neighbourhood effects are mediated through or confounded by the school context, as the neighbourhood variance clearly diminishes upon distinguishing the school level. The results of the cross-classified models in Table 3 indicate that there is a large amount of overlap in the variance associated with the neighbourhood and school level. Although the neighbourhood-level variance diminished dramatically,

Examining neighbourhood and school effects simultaneously 117 the size of the ICCs, particularly for ethnic minority students, remain non-trivial. For ethnic minority students, the potential for effects of the neighbourhood and school context appears to be greater than for native Dutch students. The ‘deviance information criterion’ (DIC) at the bottom of the table is used to compare the fit and complexity of the models, with lower values indicating a better model fit. The cross-classified models reveal a clear improvement in the fit relative to the models in which just the neighbourhood or the school levels were included, suggesting that both contexts should be considered when predicting youth achievement.

Table 3. Unconditional models: Between-neighbourhood and between-school variance in Year 3 achievement

Model 1 Model 2 Model 3 Neighbourhoods as Schools as NH and SCH as cross- level-2 units level-2 units classified level-2 units Native Non-native Native Non-native Native Non-native Variance Level 1 Individual 71.71 65.54 64.38 64.39 62.24 59.94 Level 2 Neighbourhood 27.40 44.46 2.38 5.04 Level 2 School 39.82 47.03 39.88 46.12 ICC Level 2 Neighbourhood 0.28 0.40 0.02 0.05 Level 2 School 0.38 0.42 0.38 0.42 Deviance information 62001.52 8262.49 61065.25 8240.56 60767.29 8157.04 criterion (DIC)

Notes. MCMC estimation, uninformative priors. N = Native Dutch 8720, ethnic minority 1177

Next, we ran 2-level neighbourhood models, first including only individual background characteristics (Model 1), and then adding neighbourhood characteristics (Model 2), displayed in Tables 4a and 4b. Most of the individual- level variables are significantly associated with achievement, both for natives and ethnic minorities. Age is negatively related to achievement level and being female is positively related; these associations appear to be somewhat stronger for ethnic minority students. The impact of family SES is as expected: higher levels of SES are associated with higher educational achievement. Registered partnership or cohabitation family structures relate negatively to educational achievement relative to married family structures, but this is only true for native Dutch students. With regard to the impact of neighbourhood variables (Model 2),

118 Chapter 4 high-SES is significantly related to educational achievement, with a considerably larger coefficient for ethnic minority students. There appear to be no effects of the neighbourhood low-SES variable for either group. For native Dutch students, there is a negative association between the second neighbourhood ethnic concentration quintile and educational achievement. Living in a small city appears to be positively related to achievement for native students. Comparing the variance values in Models 1 and 2 with the unconditional neighbourhood model in Table 3, we can see that the individual-level variables explain a far greater amount of between-neighbourhood variance than the neighbourhood predictors, reflecting the large variation in individual characteristics across neighbourhoods. The unique contribution of neighbourhood variables to the explained between-neighbourhood variance in Model 2 is around 4 percent for ethnic minorities and 2 percent for natives. Model 3 (Tables 4a and 4b) is a 2-level school model with individual and school characteristics. The individual-level coefficients are similar to those in the 2-level neighbourhood models in terms of directions and significance, however they are smaller in size, as differences in the schools that youth attend appear to explain some of the effects that were attributed to background characteristics, particularly family SES. The measures of high and low school SES are significantly associated with achievement for both groups of students. For native Dutch students, there is a negative association between attending a school with a high concentration of ethnic minorities (4th quintile) and educational achievement. Neither school denomination nor school type appears to be significantly associated with achievement. We combine the school and neighbourhood models into a cross-classified model in Model 4. Individual background variables show similar associations as in the previous models. The interesting differences are to be found at the context level. The associations with the school context do not differ much from the 2-level school model, except that for ethnic minorities, high-SES at the school level is no longer statistically significant. Low school SES is still strongly and negatively related to educational achievement for both groups of students. For native Dutch students, there is still a negative association between school ethnic minority concentration and achievement (for the 4th quintile). The coefficient for neighbourhood high-SES has dropped to non-significance for both groups, as has the coefficient for neighbourhood ethnic minority concentration in the native Dutch model. There are no significant neighbourhood composition variables remaining for either group; however, the variable indicating the wider city setting is still associated with achievement for native youth, with big and small cities associated positively with achievement levels, relative to medium-sized cities.

Examining neighbourhood and school effects simultaneously 119 0.18 (0.30) 3.84 (4.70) -0.38 (0.35) -0.03 (0.28) -1.63 (0.86) 30.06 (2.72) odel 5 -1.91 * (0.81) -2.47 * (0.99) M -1.14 ** (0.44) 0.61 *** (0.01) 1.71 *** (0.14) 0.93 *** (0.33) 1.64 *** (0.35) 2.40 *** (0.40) -0.68 *** (0.16) -6.97 *** (2.74) prior achievement Cross-classified with 0.14 (0.34) odel 4 -0.10 (0.43) -0.61 (0.36) -1.38 (1.16) -1.49 (1.18) 88.29 (3.48) M -2.84 * (1.40) 14.28 * (6.89) Cross-classified 1.23 *** (0.17) 1.98 *** (0.40) 3.67 *** (0.43) 4.97 *** (0.49) -2.60 *** (0.20) -1.57 *** (0.53) -20.96 *** (4.28) odel 3 0.19 (0.34) -0.06 (0.43) -0.62 (0.36) -1.63 (1.26) -1.65 (1.29) 87.71 (3.19) M -3.02 * (1.53) 2-level school -1.53 ** (0.54) 1.21 *** (0.17) 2.02 *** (0.40) 3.69 *** (0.42) 4.95 *** (0.49) 15.95 ** (6.40) -2.62 *** (0.20) -20.11 *** (3.65) 2-level odel 2 0.35 (0.47) 0.07 (0.38) 95.73 (2.94) M -1.06 * (0.39) 1.21 *** (0.19) 3.39 *** (0.43) 6.24 *** (0.46) 8.49 *** (0.53) -3.94 *** (0.21) -2.19 *** (0.59) neighbourhood 0.38 (0.47) 0.01 (0.38) 97.91 (2.86) -1.04 * (0.39) odel 1 1.21 *** (0.19) 3.51 *** (0.43) 6.46 *** (0.46) 8.81 *** (0.53) -3.99 *** (0.22) -2.27 *** (0.59) M 2-level neighbourhood, individual characteristics Multilevel and cross-classified models of neighbourhood and school effects on educational achievement, native Dutch students

Secondary education, lower stream Secondary education, higher stream Higher professional education University or postgraduate Registered partnership, cohabitation Divorced, widowed, never married Missing/unknown Q2 Q3 Q4 Year 1 Year achievement Age Gender (1=girl, 0=boy) Family SES (ref: Primary school or less) Family structure (ref: Married) Low-SES High-SES Ethnic minority concentration (ref: Q1, least) able 4a. Fixed effects Constant Parameters Level-1 (student-specific) Level-2 (school) T

120 Chapter 4 56877.04 0.53 (1.16) 0.41 (0.86) 0.60 (1.54) 0.16 (1.33) 0.09 (0.40) 0.17 (0.45) 0.67 (0.39) 0.37 (0.29) -0.77 (0.70) -0.59 (0.64) -1.17 (1.13) -1.27 (0.67) -0.17 (0.34) -0.07 (0.37) 1.24 ** (0.25) 4.58 *** (0.94) 39.84 *** (0.63) 60285.11 0.02 (1.64) 0.13 (0.57) -0.60 (1.63) -1.89 (1.06) -1.62 (0.97) -1.41 (1.24) -1.76 (1.61) -1.35 (1.06) -0.40 (1.90) -0.73 (0.43) -0.73 (0.46) -0.19 (0.50) 1.34 ** (0.49) 1.09 ** (0.36) 1.89 *** (0.42) 58.90 *** (0.96) 10.82 *** (2.08) 60543.70 -0.77 (1.60) -1.84 (1.02) -1.77 (0.94) -0.81 (1.25) -2.41 (1.63) -1.35 (0.99) 1.38 ** (0.44) 0.89 ** (0.31) 60.66 *** (0.92) 10.92 *** (1.97) 61254.80 0.97 (0.69) 0.75 (0.46) -1.97 (2.36) -0.86 (0.60) -0.23 (0.62) -1.33 * (0.56) 7.15 *** (1.95) 1.57 *** (0.38) 65.81 *** (1.10) 15.15 *** (1.15) 61265.94 65.89 *** (1.10) 15.76 *** (1.10) Q5 (most) Public Protestant Other Reform Q2 Q3 Q4 Q5 (most) Small city Big city School denomination (ref: Catholic) School type (1=multiple track, 0=single track) Low-SES High-SES Ethnic minority concentration (ref: Q1, least) Setting (ref: Medium-sized city) Level-2 (neighbourhood) Variance Parameters Individual-level variance Between-neighbourhood variance Between-school variance DIC Notes.MCMCestimation, uninformative priors. Standardparentheses.in0.001.errors 0.01,are***p 0.05,and

Examining neighbourhood and school effects simultaneously 121 4.13 (6.94) 0.10 (0.73) 0.50 (0.59) -0.67 (1.82) -0.24 (1.89) -0.75 (1.02) -0.67 (0.63) -0.04 (0.59) -0.79 (0.65) 42.12 (6.60) odel 5 -8.65 * (1.35) M 2.11 *** (0.87) 1.83 *** (0.41) 0.52 *** (0.03) -1.44 *** (0.38) prior achievement Cross-classified with odel 4 1.42 (0.84) -1.78 (2.13) -1.81 (2.24) -1.68 (1.17) -1.18 (0.74) -0.73 (0.69) -0.99 (0.73) 14.71 (8.17) 86.85 (6.95) 1.48 * (0.66) M Cross-classified 3.82 *** (0.96) 1.61 *** (0.47) -2.82 *** (0.43) -18.20 *** (4.62) odel 3 -1.50 (2.14) -1.75 (2.21) -1.79 (1.17) -1.26 (0.73) -0.74 (0.67) -0.93 (0.75) 89.81 (6.28) 1.61 * (0.80) M 2-level school 15.99 * (7.91) 1.66 ** (0.68) 4.14 *** (0.94) 1.66 *** (0.46) -2.86 *** (0.46) -18.14 *** (4.49) 2-level odel 2 -1.73 (1.27) -1.33 (0.83) -1.37 (0.74) -1.10 (0.82) 93.75 (7.03) M 7.35 *** (1.06) 1.55 *** (0.51) 3.16 *** (0.73) 3.97 *** (0.90) -4.07 *** (0.45) neighbourhood -1.93 (1.27) -1.66 (0.83) -1.48 (0.74) -1.18 (0.82) 98.15 (7.03) odel 1 8.56 *** (1.06) 1.68 *** (0.51) 3.60 *** (0.73) 4.85 *** (0.90) -4.11 *** (0.45) M 2-level neighbourhood, individual characteristics Multilevel and cross-classified models of neighbourhood and school effects on educational achievement, ethnic minority students

Q3 Q2 University or postgraduate Divorced, widowed, never married Missing/unknown Registered partnership, cohabitation Secondary education, higher stream Higher professional education Secondary education, lower stream Ethnic minority concentration (ref: Q1, least) High-SES Low-SES Family structure (ref: Married) Family SES (ref: Primary school or less) Gender (1=girl, 0=boy) Year 1 Year achievement Age able 4b. Level-2 (school) Level-1 (student-specific) Parameters Fixed effects Constant T

122 Chapter 4 7790.95 0.26 (0.77) 1.61 (1.19) 2.20 (3.73) 2.28 (2.43) 0.13 (2.44) 1.92 (2.44) 1.08 (2.48) 3.23 (2.51) 0.68 (1.34) -0.36 (0.92) -1.70 (1.01) -2.67 (3.72) -1.38 (1.07) -1.28 (1.07) -0.62 (1.98) -0.07 (2.18) 7.09 *** (1.94) 43.92 *** (2.12) 8063.44 0.56 (1.08) 0.89 (0.91) 2.16 (4.32) 4.68 (4.28) 2.74 (2.89) -0.09 (2.75) -2.89 (2.76) -1.21 (2.77) -1.41 (2.88) -1.97 (1.16) -1.75 (1.27) -1.81 (1.27) -0.43 (1.59) -2.62 (2.37) -1.98 (2.62) 4.16 * (1.89) 55.40 *** (2.89) 10.03 *** (2.84) 8146.15 2.18 (2.91) -1.75 (1.23) -2.11 (1.23) -0.79 (1.59) -1.91 (1.29) -2.37 (2.31) -1.69 (2.59) 59.34 *** (2.59) 10.41 *** (2.87) 8150.12 1.98 (3.31) 1.46 (3.31) 1.84 (3.34) 1.31 (0.82) -0.47 (0.84) -0.71 (3.29) -0.69 (4.92) 59.65 *** (3.60) 24.15 *** (4.21) 13.76 *** (4.79) 8161.61 60.24 *** (3.94) 25.21 *** (4.21) Big city Q3 Q4 Q5 (most) Q2 Small city Protestant Other Reform Public Q5 (most) Q4 Ethnic minority concentration (ref: Q1, least) Setting (ref: Medium-sized city) High-SES Low-SES School type (1=multiple track, 0=single track) School denomination (ref: Catholic) Variance Parameters Individual-level variance Between-neighbourhood variance Between-school variance DIC Level-2 (neighbourhood) Notes.MCMCestimation, uninformative priors. Standardparentheses.in0.001.errors 0.01,are***p 0.05,and

Examining neighbourhood and school effects simultaneously 123 In Model 5 prior achievement was added. As expected, the fit of the models improves substantially, since prior achievement is a strong predictor of later achievement. The coefficients for age and family SES are still significant but have been largely attenuated by prior achievement, as these factors are also related to earlier learning and achievement. The positive effect of being female is still significant and has become larger, indicating that being female is especially associated with higher achievement during these first years of secondary school. The impact of school SES has been considerably attenuated; the coefficient for low-SES has decreased by 53 percent for ethnic minorities and 67 percent for natives, but is still statistically significant and substantial. The coefficient for high-SES (i.e. native Dutch model) is no longer significant. As in Model 3, the neighbourhood composition variables do not have any significant associations with educational achievement. Differences between the urban settings for native youth are no longer significant. Comparing the coefficients for prior achievement between the two groups, we see that prior achievement is a stronger predictor of native youths’ Year 3 achievement than of ethnic minorities’. In our final model we tested for cross-level interaction effects between characteristics of neighbourhoods and schools (e.g. school low-SES X neighbourhood low-SES), but found no significant effects or improvements in the model fit (and therefore left these out of the model). This is not surprising, given the lack of significant main effects of the neighbourhood variables and the very small between-neighbourhood variance remaining, which makes detecting such interactions unlikely (Goldstein, 2003). Thus, we find no support in these models for the notion that one context moderates the effects of the other. It appears that in our sample, once taking school, individual and family background characteristics into account, there is no significant direct or interacting effect of the neighbourhood milieu on youths’ educational achievement. In our final model, we also tested for non-linearities of the SES context variables by collapsing the variables into categories, but found no support for non-linearity (not shown in the models); therefore, at least after taking prior achievement into account, the association between low school SES and educational achievement appears to be a linear one. The overall amount of explained variance can be partitioned into the proportional reduction of original (unconditional) variance at the individual, neighbourhood and school level that is accounted for in the final model (Goldstein, 2003). For native youth, our final model explains 0.36 of the original individual-level variance, 0.48 of the between-neighbourhood variance, and 0.89 of the between-school variance; for ethnic minority youth these figures are 0.27, 0.68, and 0.85, respectively. The neighbourhood variables themselves explain very little of the total variance; nearly all of the variance originally associated with

124 Chapter 4 neighbourhoods was explained by school and individual factors. This indicates that most of the observed variation in achievement between neighbourhoods is accounted for by differences in the schools attended and the population characteristics across neighbourhoods.

4.7 Discussion and conclusion Theoretically and intuitively, the social contexts in which people live and grow up are expected to have an impact on their ‘outcomes’. In this paper we paid attention to educational achievement as the outcome, and to school and neighbourhood contexts as the social environments that help to shape this outcome. We aimed to better understand the possible links between neighbourhood and school effects, and specifically to test whether the influence of youths’ neighbourhood environments might be transferred through the school context, implying the school’s role as an ‘institutional mechanism’ of neighbourhood effects. As the literature describes several possible relationships between neighbourhoods and schools and their potential effects on youth, we also tested for moderating or interaction effects (i.e. when the effects of one context vary as a function of the other). When considered separately, we find that both the neighbourhood and the school context are significantly associated with youths’ educational achievement. However, when the contexts are entered into the analysis simultaneously, the model improves in terms of fit, but the introduction of the school context reduces the association between the neighbourhood and achievement. In other words, upon considering youths’ concurrent membership in both schools and neighbourhoods, the associations between the school and educational achievement remain significant, whereas the associations with the neighbourhood diminish and lose their significance. Does this finding suggest that the school is a mediating factor in the neighbourhood’s effect on youth achievement? We believe that these results point to schools as both mediators and confounders of the neighbourhood effect. While some students are educated locally – and thus, their schools could mediate the effects of their neighbourhoods, other students do not attend schools in their home neighbourhood, and thus, our models appear to pick up on the confounding of neighbourhood and school effects. In both cases, the main point is that school and neighbourhood effects are related, and in particular, without consideration of the former, the latter is likely to be substantially overestimated.

Examining neighbourhood and school effects simultaneously 125 We could not find support, however, for the notion that neighbourhood and school variables interact in their influence on youth achievement. Although recognition of the neighbourhood context improves the fit of the model, it appears that once taking individual, family and school characteristics into account, the neighbourhood does not play a significant direct or interacting role in predicting achievement, answering the second and third research questions. The dominant role of the school context (versus the neighbourhood) in predicting youth educational achievement is not that remarkable, given that schools function mainly as sites of educational learning. However, because of the proximity of neighbourhood and school for many students, school composition will be highly informed by neighbourhood composition, and through that relation the neighbourhood may be regarded to have an indirect impact. There may also be ways in which local neighbourhood context affects the internal functioning and organization of schools (e.g. Lupton, 2004), however, these were not explored in this paper. While the size and significance of some of the coefficients in our model differed between native and ethnic minority youth, the overall picture of the relation between neighbourhood and school effects did not differ. In line with other studies (e.g. Pong and Hao, 2007), we found family SES to have a stronger and clearer association with native Dutch students’ achievement than with ethnic minorities’. This suggests that socioeconomic background does not translate into educational outcomes for non-natives to the extent it does for natives, or that SES may be measuring different things for these two groups. We also find prior achievement to be a stronger predictor of native students’ achievement than of ethnic minorities’. Delving more deeply into the differences between (and within) these groups and their experiences in education is an area for future research; moreover, our dichotomous grouping of ‘native’ and ‘ethnic minority’ will mask much heterogeneity within these two groups. We tested an important thesis in the neighbourhood effects literature, using a large-scale dataset with neighbourhood and school information and highly reliable measures of achievement. However, in addition to these strengths, our study has a number of limitations. We attempted to take some potential selection bias into account by controlling for prior achievement scores; however, this is likely to be a crude adjustment for selection effects. Although recent work suggests that taking even a fairly simple set of individual and family factors into account, including SES and ethnic background, “may make for a reasonable test of neighborhood influences” (Sampson and Sharkey, 2008: 25), selection bias remains a potential threat to our findings. While better accounting for selection effects would have been preferred, our main aim was to test for the mediation of

126 Chapter 4 neighbourhood effects through the school, and we believe that our results provide important insights into that question, even if only serving to show patterns of association rather than causation. Moreover, selection effects are of substantive interest in themselves and an important challenge for neighbourhood and school effects researchers is to better understand the non-random sorting of individuals into these contexts, rather than to just control for the ‘selection problem’. In particular, caution should be exercised when interpreting the effects of the school coefficients, not only because of potential selection bias, but also because we did not take a large set of school factors into account, specifically process and relational attributes. Thus, our results say nothing about which processes may be driving the association between school SES and achievement; qualitative and quantitative research suggests that these may include school organization, classroom climate and ethos, teacher instruction and peer influences (Gewirtz, 1998; Lupton, 2004; Thrupp et al., 2002). Our model is based on a number of other assumptions. We relied on readily available official data to measure neighbourhood characteristics. To the extent that these serve as weak proxies for the processes at work in neighbourhoods that are thought to be important for young people, we may be undercutting the role of the neighbourhood. While we shed some light on the relation between neighbourhood and school effects, it is up to future studies to examine the other processes and pathways that might transfer or moderate neighbourhood influences. Furthermore, while we considered some potential effect heterogeneity (i.e. across native/ethnic minority background), our models still tested for average effects across a large sample of youth; for specific types of youth and contexts (e.g. youth attending a neighbourhood versus a non-neighbourhood school; different neighbourhood and school types; different school levels), the role of the neighbourhood or school may be different. Examining the possibility of these more nuanced and less generic effects is an important avenue for future research. This calls for theories and methods that account for the varied and complex interdependencies among young people and their social contexts. Moreover, the relationships among youth and their families, schools, neighbourhoods, and decisions such as school choice, are also set within local and national institutional and policy contexts (Arum, 2000). Our findings are based on a context in which universal and compensatory funding measures for schools exist, in addition to significant welfare state interventions at the family and individual level. Neighbourhood segregation levels are comparatively modest in the Netherlands (Musterd, 2005); however, levels of segregation and stratification in schools are higher, both in absolute terms and relative to comparable measures in the US (Ladd et al., 2009). Our

Examining neighbourhood and school effects simultaneously 127 findings corroborate those of Kauppinen (2008) and Brännström (2008) in other European welfare states, and are also supportive of Pong and Hao’s (2007) work in the US in terms of mediation, although Pong and Hao found neighbourhood effects to persist for some groups, even after the consideration of school factors. How neighbourhood and school effects and their association vary across different contexts, and what causes this variation, remain to be seen. One of the crucial findings of our analysis is that models of neighbourhood effects on young peoples’ outcomes that fail to consider the school context are likely to seriously overestimate direct neighbourhood effects, and leave potential pathways of neighbourhood effects unexamined. While research on neighbourhood effects on child and youth outcomes largely assumes that the school context is an important institutional mechanism of the neighbourhood’s effect, this is rarely explicitly tested. In line with the results of other studies (e.g. Brännström, 2008; Kauppinen, 2008; Pong and Hao, 2007), our findings underscore the importance of including the school context in models of neighbourhood effects on children and youth. Recognizing both contexts has important implications for how we understand the roles of schools and neighbourhoods and how we formulate policy responses.

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130 Chapter 4

5 The social mix debate: What does it mean for neighbourhood effects research? Abstract

The increasing promotion of neighbourhood social mixing as a potential remedy for urban social problems has given rise to reinvigorated debate about the expectations, problems, and limits of social mixing initiatives. Critics call into question the fundamental assumptions underlying neighbourhood social mixing strategies, the contradictions and ambiguities about how social mix should translate into beneficial outcomes for residents, and the insufficient attention given to the social costs involved, especially for the populations excluded from newly mixed and revitalized neighbourhoods. In this debate, scholars point out that much of the research on ‘neighbourhood effects’ and the effects of ‘concentrated poverty’ has advanced the notion that living among poor people perpetuates individual poverty, whereas middle-class neighbours provide benefits. This field of research is thus seen as lending theoretical and empirical support to social mixing policies. After briefly reviewing how social mixing is currently being promoted at the neighbourhood level and summarizing key points from the growing critique of social mixing and poverty deconcentration strategies, this paper asks what the social mix debate means for neighbourhood effects research.

Submitted for review. Co-authored by Sako Musterd.

134 Chapter 5 5.1 Introduction ‘Socially mixed neighbourhoods’ have emerged as a major urban policy goal in cities throughout Western Europe, North America and elsewhere. Social mix (and in many instances, ethnic mix) is promoted through a range of policy interventions, from the large-scale restructuring of low-income neighbourhoods into mixed-tenure, mixed-income communities, to planning regulations that seek to intervene in the social makeup of targeted neighbourhoods (Rose, 2004; Davidson, 2008; Lees, 2008). While these policies serve a number of objectives and interests, one dominant objective is to alleviate concentrations of low-income households and thus, the individual and neighbourhood problems perceived to be caused or exacerbated by these concentrations. In step with the renewed enthusiasm for social mixing on the part of urban governance and other proponents, has been a growing body of scholarship which challenges the theoretical groundings, empirical support and ideological underpinnings of social mixing strategies (Goodchild and Cole, 2001; Tunstall, 2003; Uitermark, 2003; Kleinhans, 2004; Rose, 2004; Andersson and Musterd, 2005; Musterd and Andersson, 2005; Joseph et al., 2007; Lees, 2008; Lupton and Tunstall, 2008; Lupton and Fuller, 2009; Goetz, 2010). Part of this work examines why social mix is increasingly endorsed, how it is politically framed and what the motives – stated and unstated – behind these strategies are (Uitermark, 2003; Lupton and Tunstall, 2008). Critics stress that the rhetoric of social mixing often camouflages state-led gentrification strategies, in which the state actively encourages and supports gentrification, typically in partnership with private actors (Lees, 2008). Particularly in Europe, advocacy of social mix is connected to renewed anxiety about ethnic segregation and integration, social cohesion, and the development of ‘parallel societies’, which are considered to pose a threat to national unity and social order (Uitermark, 2003; Münch, 2009; Phillips, 2010). Another set of critique interrogates the policy objectives and evidence base for mix strategies, with a major focus on whether social mixing is an effective strategy to improve the lives of poor people (Andersson and Musterd, 2005; Musterd and Andersson, 2005; Joseph et al., 2007; Goetz, 2010). When assessed next to the existing empirical literature, the claims that social mixing will improve the economic and social circumstances of low-income residents are at best ambiguous, and at worst, misleading (cf. Tunstall, 2003; Kleinhans, 2004; Andersson and Musterd, 2005; Joseph et al., 2007; Goetz, 2010). In this critique, a link has been drawn between the academic discourse on ‘neighbourhood effects’ and ‘concentrated poverty’ and the increased policy emphasis on deconcentrating low-income neighbourhoods through social mixing

The social mix debate and neighbourhood effects 135 (Musterd and Andersson, 2005; Imbroscio, 2008; Lipman, 2008; Lupton and Fuller, 2009). This field of research is widely seen as lending theoretical support to social mixing and poverty deconcentration strategies. Writing about the US, Curley (2005: 105) explains:

Theorists and policymakers have taken [William Julius] Wilson’s poverty concentration thesis and argued that if concentrated poverty contributes to unwanted behavior and social ills, then deconcentrating poverty should reverse this effect. This rationale has led to recent housing dispersal programs and mixed-income housing initiatives that intend to deconcentrate poverty, and consequently, reduce the social problems attributed to poverty concentration in urban public housing developments.

Discussing urban policies in Western Europe, van Ham and Manley (2010: 258) also comment that:

[t]he neighbourhood effects discourse has had a major impact on urban neighbourhood and housing policies and has influenced governments to spend large sums of money on area-based policies to tackle poverty. Creating neighbourhoods with a balanced socio- economic mix of residents is a common strategy to tackle assumed negative neighbourhood effects.

Others have questioned whether neighbourhood effects discourse has actually inspired, or is rather helping to legitimize, social mixing policies and the wider turn towards area-based policy (c.f. Fallov, 2010; Smith and Easterlow, 2005: 176). This paper examines the place of neighbourhood effects discourse in the broader debate on neighbourhood social mixing initiatives. In the first part of the paper, we briefly discuss how and why social mix is currently applied at the neighbourhood level, focusing on North America and Western Europe. In the second part, we summarize key points from recent critiques of mix policies, followed by a discussion of the field of neighbourhood effects research, and its place in the social mix debate. Although notions of neighbourhood effects and the (causal) effects of concentrated poverty have, to some extent, been taken up by policymakers in their conceptualizations of the ‘problem’ (i.e. social problems caused by spatially concentrated poverty or socially unbalanced neighbourhoods) and in their justification of the ‘solution’ (i.e. social mixing and poverty deconcentration initiatives), these notions are themselves contested, and

136 Chapter 5 thus the social mix debate offers a useful window into a broader discussion of scholarly research on neighbourhood effects and concentrated poverty. We offer suggestions for future directions in neighbourhood research and in the final section we draw conclusions.

Social mixing: 5.2 An old ideal, a new delivery The origins of social mix as a planning ideal can be traced back to nineteenth century Britain, with its town plans for ‘socially harmonious’, mixed communities (Sarkissian, 1976). The concept shifted in and out of popularity over the years, re-emerging in the 1990s, largely in response to the negative effects tied to poverty concentration and large, monotonous public housing developments (August, 2008). Social mix and poverty deconcentration became widely touted as means of overcoming the difficulties in poor neighbourhoods, and emerged as key components of strategies to ‘revitalize’, ‘restructure’ and ‘regenerate’ these areas (Smith, 2002). These strategies, which variously promote ‘income mix’, ‘social diversity’ and ‘social balance’, seek to deconcentrate low-income neighbourhoods by attracting higher-income households, primarily through housing and tenure diversification (Kleinhans, 2004; Rose, 2004; Joseph et al., 2007; Davidson, 2008; Lees, 2008). The most ambitious plans promoting social mix are the large-scale neighbourhood restructuring and public housing redevelopment schemes that seek to transform areas of low-income and social housing into mixed-tenure, mixed-income neighbourhoods (Kleinhans, 2004; Goetz, 2010). Typically through a combination of selective housing demolition, refurbishment, tenure conversion and new construction, these programmes decrease the share of low-cost social housing and increase the share of more expensive social and owner-occupied housing. The new owner-occupied dwellings are expected to attract higher- income households into the area, as well as retain upwardly mobile residents. Tenants in social housing units slated for demolition are forced to relocate (Bolt and van Kempen, 2010). The largest and most heavily funded of these programmes are in the US (Goetz, 2003; Curley, 2005), Great Britain (Kleinhans, 2004; Lupton and Tunstall, 2008) and the Netherlands (Uitermark, 2003; Bolt and van Kempen, 2010; van Gent et al., 2009) – as exemplified by HOPE VI (Housing Opportunities for People Everywhere), the ‘New Deal for Communities’, and the prevailing Dutch ‘Big Cities Policy’, respectively; programmes also exist

The social mix debate and neighbourhood effects 137 in Canada (August, 2008), Australia (Arthurson, 2005), France (Blanc, 2010) and elsewhere1. These programmes have ambitious social goals; HOPE VI aims to enhance residents’ economic ‘self-sufficiency’, while the focus in Europe and elsewhere is more generally on the ‘upward social mobility’ of residents (Curley and Kleinhans, 2010). In the case of demolition, it is generally assumed that any relocation provides residents ‘inherent benefits’ (Goetz, 2010), as they are not obliged to relocate to any specific kind of neighbourhood, at least not in the Dutch or US case (ibid.; Bolt et al., 2009). Thus, households can move to another poor neighbourhood and many do so. Based on their study of the residential patterns of households forced to move because of restructuring in the Netherlands, Bolt et al. (2009: 510) assert that “[d]isplacement moves tend to be between similar neighbourhoods; such relocations can be characterized as ‘horizontal’ moves”. In a HOPE VI resident tracking study, Popkin et al. (2004: 407) report that about 40 percent of the tenants forced to relocate “have ended up in other, distressed high-poverty neighbourhoods”. In these programmes, social mixing is one facet of a broader, ‘integrative’ approach to neighbourhood regeneration, in which extra services and support are offered to residents, alongside investments in housing and infrastructure (Lupton and Fuller, 2009; Curley and Kleinhans, 2010). The weight of private- market finance and the role of private actors set these programmes apart from past urban renewal schemes (Smith, 2002; Tunstall, 2003). Whereas urban renewal in the 1950s, 1960s and 1970s was entirely dependent on public financing, restructuring efforts today rely heavily on private financial capital and public-private partnerships (Smith, 2002). Accordingly, the emphasis has shifted from building (primarily) social housing to promoting homeownership. Current programmes also typically aim for a more transformative change in neighbourhoods than more recent regeneration schemes. As Lupton and Tunstall (2008: 107) explain, although past regeneration programmes in the UK may have encouraged tenure diversification and social mix, they “aimed to improve rather than fundamentally transform poor neighbourhoods”, whereas current initiatives explicitly aim to ‘transform’ and ‘remodel’ low-income neighbourhoods.

1 Although there are common elements in these restructuring programmes – particularly the emphasis on ‘income mixing’ and social housing deconcentration – they naturally vary in their specific ap- proaches. The extent of demolition appears to be highest in the Netherlands and the US. According to Curley and Kleinhans (2010: 373-374), by 2006 more than 78,000 units had been demolished under HOPE VI and another 10,400 were lined up for redevelopment; only 55 percent of the replace- ment units will be ‘deeply subsidized’ housing. In the Netherlands, more than 121,000 social rented dwellings have been demolished since 1997 under neighbourhood restructuring; the number of new constructions are higher, although the majority are more expensive rental or owner-occupied dwellings (ibid.). For a different policy approach to social mixing, which does not involve demolition, see Andersson et al. (2010) on Sweden.

138 Chapter 5 At a smaller scale, social mix is also promoted through social housing allocation policies and planning regulations that aim to intervene in the population composition of selected neighbourhoods. A recent ‘anti-segregation’ policy in the Netherlands is an example of such an approach (Musterd and Ostendorf, 2008; van Eijk, 2010). First adopted in Rotterdam and later approved by the national government, this policy allows municipalities to refuse the settlement of unemployed or underemployed households (via an income regulation) into the rental housing of targeted neighbourhoods that are deemed to have too large of a concentration of such groups (ibid.). As van Eijk (2010: 5) explains, this policy was justified as a means of preventing these neighbourhoods from becoming ‘unliveable’ due to the concentration of poverty and the social problems alleged to be exacerbated by these concentrations, including unemployment, school drop-out, crime, nuisance and anti-social behaviour. Although the official focus is on income, the intention is nevertheless clear that the policy aims to reduce concentrations of low-income ethnic minority groups. The policy documents connect these ‘concentration neighbourhoods’ to the problematic integration of ethnic minorities (ibid.: 5-6). In the policy discourse, social mix is presented as leading to a win-win scenario: benefits for the neighbourhood and concerned actors, and positive outcomes for residents (Kleinhans, 2004; Davidson, 2008; Goetz, 2010). As many observers have pointed out, social mix is rarely advocated in higher-income areas (Smith, 2002; Lees, 2008); thus, it is not ‘social mix’ per se that is advocated, but poverty (or social housing) deconcentration. Social mixing initiatives seek to improve both place-based conditions and people-based outcomes. As Lupton and Tunstall (2008: 113) explain, the ‘Mixed Communities Initiative’ in Great Britain aims to “create a more sustainable mix of housing types and tenures and to address deep-seated problems of worklessness, low skills, crime, poor environments and poor health”. The HOPE VI programme in the US, which redevelops public housing projects into mixed-income neighbourhoods, was also created “to produce two major types of beneficial outcomes: better outcomes for the residents of distressed public housing projects, and better neighborhood conditions in the projects themselves and their surrounding neighborhoods” (Goetz, 2010: 140). What are the underlying assumptions and expectations of these initiatives? What theoretical notions are embedded in these approaches to social mixing and poverty deconcentration? How are these strategies justified? In the next section we examine the discourse surrounding social mix and the apparent assumptions underlying these initiatives with regard to the problems they claim to tackle and the solutions they endorse.

The social mix debate and neighbourhood effects 139 Assumptions, expectations and discourses 5.3 of neighbourhood social mixing While there is not one coherent discourse underpinning social mix and poverty deconcentration interventions, there are a number of common notions and constructions regarding the causes of and solutions to urban social problems. Perhaps most distinctly, these policies are concerned mainly with the neighbourhood and spatial manifestation of social problems, rather than their structural properties. In the policy discourse, a strong emphasis is placed on the spatial character and causes of social phenomena such as poverty, social exclusion, and integration, and on the spatial concentration of certain groups. As Lupton and Tunstall (2008: 110) explain, in the context of British policy, “[e]mphasis is given to the spatial ordering of problems, not as a manifestation of structural deficiencies, but in terms which appear to emphasize the spatial behaviour of people: ‘concentration’, ‘clustering’, ‘pockets of poverty’, ‘segregation’”. Social mixing initiatives are premised on the idea that urban problems and individual circumstances can be improved by altering the social makeup of poor neighbourhoods. The spatial concentration of low-income groups is seen as a source of problems, and thus, social mixing and deconcentration are viewed as part of the solution. According to some policy texts, in the absence of social mix, low-income neighbourhoods may run the risk of heading into a “downward spiral” (Uitermark, 2003; van Eijk, 2010). Texts also make reference to the ”absorption capacity” of neighbourhoods or certain “tipping points” with respect to the population composition, which are “meant to mark the onset of the quarter’s disintegration” (Münch, 2009: 446). In a number of countries, the pursuit of social mix is entwined with the debate on immigrant integration and political anxieties about the interrelationships between residential segregation, social cohesion and integration (for a discussion of European countries, see Phillips, 2010; Uitermark, 2003; Bolt et al., 2009). Residential segregation (of ethnic minority groups) has come to be viewed as inherently undesirable and is often automatically assumed to be symptomatic of failed integration and potentially threatening to social order and civil unity (Phillips, 2006; Wacquant, 2008; van Eijk, 2010). While some policy texts make a direct reference to the existence or threat of ‘neighbourhood effects’, others imply their existence (Curley, 2005; Fallov, 2010; Lupton and Tunstall, 2008). Neighbourhood effects discourse is also called upon to explain how the benefits from social mixing are meant to materialize. As Fallov (2010: 3) notes, the language of policy is not fixed, and the incorporation of academic terms is not simply an appropriation, but a recontextualization, “[i]n the

140 Chapter 5 sense that the academic concepts are inserted into the existing policy framework emphasizing the particular meanings of the concepts that resonate with the policy narratives”. Based on her analysis of Danish and British neighbourhood and social exclusion policies that aim to cultivate local “community capacities” and “neighbourhood-wide social capital” as a means of overcoming social exclusion, Fallov (ibid.) argues that people-focused explanations for neighbourhood effects, rather than the structural explanations (e.g. lack of job opportunities, poor services), have been appropriated and inserted into this policy narrative “resulting in an individualized and spatialized perspective on exclusion. This means that area effects are used to legitimize the area-based approach to tackling social exclusion”. Individual social problems have become rendered as neighbourhood phenomena, and both problem and solution are seen to lie, at least in part, in the neighbourhood. According to Lupton and Fuller (2009: 1017), the ‘Mixed Communities Initiative’, in place since 2005 in Great Britain, has adopted the

thesis that ‘concentrated poverty’ (or in some iterations, concentrated social housing tenure) is the problem and ‘de-concentration’ the solution. In a way unprecedented in the earlier years of New Labour, UK policy documents from 2005 onwards draw heavily on the notion of ‘neighbourhood effects’, defined as the ‘additional disadvantages that affect poorer people when they are concentrated in poor neighbourhoods’.

In the US, Goetz (2002: 161) asserts that over the course of the 1990s, ‘concentrated poverty’ became “the organizing theme for much urban policy at both the federal and local levels”, which led to a reorientation of housing politics inwards, to the neighbourhood and its specific composition. As a result, the problems of neighbourhoods became internalized and the solutions also became directed internally, with little attention given to the structural factors that concentrated poverty in the first place (ibid.). Crump (2002) voices similar sentiments; he argues that the extensive use of the concept of ‘concentrated poverty’ in the US as shorthand for the conditions in poor neighbourhoods has led to an important theoretical slippage, whereby concentrated poverty has come to serve as a spatial metaphor that hides from view the complex political, social and economic processes that drive poverty, offering instead a simplistic spatial solution: deconcentrate it. Although concentrated poverty may well exacerbate or worsen the conditions of individual poverty, they argue that it has come to be seen as an underlying cause of poverty. They demonstrate how policymakers

The social mix debate and neighbourhood effects 141 have used the concentration of poverty argument to justify the ‘demolish and disperse’ approach to public housing redevelopment, in the form of the HOPE VI programme (see also Goetz, 2003; Imbroscio, 2008; Lipman, 2008). To explain the causal assumptions embedded in the policy literature regarding individual and neighbourhood-based outcomes, a number of scholars have used the framework of neighbourhood effects (see Joseph et al., 2007 for an overview; see also Tunstall, 2003; Kleinhans, 2004; Andersson and Musterd, 2005; Goetz, 2010). Through various institutional and social-interactional mechanisms, such as shared norms and values, role modelling, peer effects, the quality and diversity of public services and institutions, and stigmatization by external actors, poor neighbourhoods are thought to exacerbate or reinforce individual poverty, while people are generally thought to benefit from living in a more affluent or mixed- income environment (Wilson 1987; Leventhal and Brooks-Gunn, 2000; Sampson et al., 2002). In mixed-income neighbourhoods, middle-class groups are thought to be resources for other residents. According to the social capital literature, people might gain from the development of ‘bridging capital’ and ‘weak ties’ to residents with higher levels of socioeconomic status, which could connect them to valuable resources and opportunities beyond their immediate social network (Briggs, 1997). Middle-class residents are also perceived to be good role models, who help to transmit conventional norms and values pertaining to work and education (Wilson, 1987). A more diverse housing stock is also expected to reduce population turnover, which could strengthen community bonds and the development of collective efficacy (i.e. mutual trust and social cohesion) and informal social control (Sampson et al., 2002). These mechanisms are thought to be important for keeping levels of crime and delinquency in check. Homeowners and higher- income residents are thought to be more likely and better equipped to advocate for the neighbourhood and its institutions and public services (Goetz, 2010). The idea is that “residents of a mixed-income community will benefit from the presence of higher-income residents, whose greater economic resources, political connections, and civic engagement should attract and compel greater attention from external actors” (Joseph et al., 2007: 393). Thus, it is widely believed that social mixing will foster better community relations and residential stability, and that lower-income residents will benefit in various ways from living amongst higher-income households. Although we have roughly outlined the mechanisms through which social mix may be expected to generate benefits for communities and residents, explaining how social mix should theoretically benefit neighbourhoods and their residents is much easier than elucidating how these notions should be translated into policy affecting real

142 Chapter 5 communities. In the next section we summarize key points from the critiques that have been directed towards social mix and poverty deconcentration initiatives, before looking more closely at the field of neighbourhood effects research.

Critiquing social mix: The political 5.4 dimensions and evidence base Social mixing initiatives have generated considerable critique (e.g. Goodchild and Cole, 2001; Andersson and Musterd, 2005; Lees, 2008). Certainly, much of this is related to the particular settings in which mix policies are launched and the specific nature of the initiatives; nevertheless, there are many common aspects. In this section we highlight four issues: (1) overstating the role of the neighbourhood, (2) blurred objectives, (3) weak evidence base, and (4) social costs.

5.4.1 Overstating the role of the neighbourhood One of the broad criticisms is that social mixing and poverty deconcentration initiatives only shift or dilute the problems they ostensibly aspire to tackle (Kleinhans, 2004; Joseph et al., 2007; Imbroscio, 2008). Intervening in the population composition of poor neighbourhoods or promoting social mixing does not address the root causes of poverty or segregation; the focus on social mixing and deconcentration as potential remedies for individual problems has been criticized for downplaying the institutional and economic constraints that individuals face, and diverting attention away from more fundamental determinants of poverty (Rose, 2004; Lupton and Tunstall, 2008). These policies overstate the role of the neighbourhood and its population composition in bringing about social problems and in resolving them. Moreover, generalized assumptions about the effects of neighbourhood segregation are problematic, for, as many commentators have explained, the links between residential segregation and social integration and inclusion are not well understood and cannot be reduced to a simple, generic formula (Musterd, 2003; Peach, 2009; Phillips, 2010).

5.4.2 Blurred objectives Social mixing strategies have garnered substantial attention from gentrification researchers, who argue that social mixing is often a euphemism for state-led gentrification (see Lees, 2008 for a comprehensive overview). Lees (2008) writes, “[i]t is ironic that a process that results in segregation and polarization – gentrification – is being promoted via social mix policies as the ‘positive’ solution

The social mix debate and neighbourhood effects 143 to segregation…the rhetoric of social mixing tends to conceal the inequalities of fortune and economic circumstance that are produced through the process of gentrification” (2008: 2463). State-led gentrification does not necessarily involve the direct displacement of residents; rather, displacement may be indirect, occurring in adjacent communities or through a change in neighbourhood resources or socio-cultural milieu (e.g. Davidson, 2008). Referring to findings from HOPE VI redevelopments that profited from local housing markets that were “poised to take off”, Goetz (2010: 152) notes that “[t]he direct displacement of public housing residents via demolition in these cases is supplemented by the indirect displacement of their neighbors via the market”. As Rose (2004: 304) points out, the “blurring of policy objectives” between “endogenous” neighbourhood revitalization and “exogenous” promotion of gentrification is also problematic, not least because this blurring of policy goals works to “fuel the scepticism” with which many people view social mix discourse. Van Gent et al. (2009) argue, in reference to a Dutch neighbourhood- based social mixing programme, that it is not clear whether the priority of the programme is to tackle neighbourhood-based problems, such as liveability, or people-based problems, such as social deprivation, and that these two issues are not as coupled as policymakers presume and do not require the same type of strategy.

5.4.3 Weak evidence base Social scientists have long been critical about the alleged benefits of social mixing and the assumed social interaction that it should foster (Gans, 1961; Sarkissian, 1976). Mere proximity does not necessarily bring about interaction between residents, especially among people of different backgrounds and lifestyles, and especially if neighbourhoods lack common spaces, activities or institutions that promote interaction (Blokland, 2003; Butler, 2003; Arthurson, 2010). Moreover, even when present, residents can opt out of local institutions. For instance, studies have shown class divisions in the school choices of families living in socially mixed areas, with middle-class parents often sending their children to (private or ‘better’) schools elsewhere (Butler, 2003). This is an important point, because it is often assumed that mix will be particularly beneficial for children and youth. However, given the system of open school choice in some countries (e.g. the Netherlands and Sweden), the increasing privatization and marketization of education (see Ball, 1998), and trends in ‘school segregation’, it is questionable whether children in socially mixed or gentrifying neighbourhoods will even attend the same schools. Spatial integration is no guarantee for social integration.

144 Chapter 5 In their literature reviews, Kleinhans (2004) and Joseph et al. (2007) find virtually no support for the notion that positive role modelling effects will occur in mixed communities, and weak support for the idea that benefits will accrue from neighbourhood-based social interaction. Studies of the HOPE VI public housing redevelopment programme reveal clear and substantial improvements in levels of neighbourhood safety and crime and the quality of housing and public space, but small or unclear gains in individual economic self-sufficiency or educational outcomes – which were explicit goals of the programme (Popkin et al., 2004; Imbroscio, 2008; Goetz, 2010). In describing these findings, Goetz (2010: 159) comments, “[t]he often complicated and extensive chain of events that must occur for individual benefits to materialize provide context for understanding the modest level of benefits documented in most studies”. The findings to date indicate that the clearest outcomes of mixed-income redevelopments are in terms of place-based revitalization, such as improved housing and physical environment, lower levels of crime and visible disorder, and increased property values (Kleinhans, 2004; Popkin et al., 2004; Joseph et al., 2007; Goetz, 2010). As commentators have pointed out, many of the public housing sites slated for redevelopment into mixed-income, mixed-tenure developments are located on prime real estate land, and such redevelopment has been found to have far-reaching effects in terms of increased property values and transformation of surrounding neighbourhoods (see Goetz, 2010: 152). While some residents will benefit from these changes, it is clear that they also serve the interests of state actors, social housing managers and private developers (see Uitermark, 2003). Moreover, many neighbourhood-level outcomes are due to population turnover and the displacement of problems, rather than the upward mobility of residents or the resolution of problems (see Kleinhans, 2004). Finally, as Goodchild and Cole (2001: 359) remark, although neighbourhood conditions may improve, the households most directly affected by attempts to secure ‘social mix’ – those priced out of the revitalized neighbourhood or forced to move because of the demolition of their home – will ironically not get the chance to share in these improvements. In the case of neighbourhood restructuring projects, this seems to be an obvious injustice when one considers the massive financial investments being poured into their old neighbourhood (e.g. new infrastructure, upgraded housing and public spaces).

5.4.4 Social costs Importantly, the negative effects that some residents and communities will incur from social mix initiatives are typically undervalued or unacknowledged in the policy discourse (Lees, 2008; Goetz, 2010). Changes in the population

The social mix debate and neighbourhood effects 145 composition of neighbourhoods and resident relocation may bring about significant social, political and financial costs for some individuals and communities, such as the fragmentation of existing social support networks and community ties, displacement and increased rents (Davidson, 2008). Imbroscio (2008) calls attention to the fact that in many cases of housing demolition due to neighbourhood restructuring, some residents are not even afforded the right or opportunity to stay put. Neighbourhood restructuring often (but not always) results in a reduction in the number of social housing units on site, so clearly not all residents who want to remain in their old neighbourhood can stay (Kleinhans and Bouma-Doff, 2008; Lupton and Tunstall, 2008). In a recent study of the relocation patterns of 490 residents forced to move due to neighbourhood restructuring in the Netherlands, Bolt and van Kempen (2010) find that about half of the residents expressed the preference to stay in the neighbourhood, but only 27 percent did so. They attribute this discrepancy to the net loss of affordable housing in the restructured neighbourhoods and the burden of moving twice. Results from a HOPE VI resident tracking study indicate that 70 percent of the tenants forced to relocate expressed the preference to return to the revitalized HOPE VI site after redevelopment, but only 19 percent did so (Popkin et al., 2004). The authors attribute this to the strict screening criteria for the new mixed-income developments, which many residents would be unable to meet, and to the major reduction in affordable housing on site (ibid.: 405).

The place of neighbourhood effects 5.5 research Many of the central notions in the policy discourse on social mix and poverty deconcentration correspond to those in the field of neighbourhood effects research (Joseph et al., 2007; Lupton and Tunstall, 2008), and in search for evidence to support or refute mix policies, scholars also turn to this field of research (Tunstall, 2003; Kleinhans, 2004; Andersson and Musterd, 2005; Musterd and Andersson, 2006; cf. references in Imbroscio, 2008; Goetz, 2010). Thus, there are several important reasons to reflect on neighbourhood effects research in the context of the current social mix debate. Although most neighbourhood effects researchers warn against inferring causality from their results, there is much talk of the ‘negative effects’ of living amongst poor people, through such things as presumably bad role models, a lack of conventional norms and values, and deviant work ethnics (Bauder, 2002). Lupton and Tunstall (2008: 114) argue that this research has “unwittingly

146 Chapter 5 lent weight to the idea that poor people are bad for each other”. Because neighbourhood effects research typically emphasizes the population composition of neighbourhoods, which often boils down to “how many poor people live there”, and highlights people-based mechanisms, they argue, “[i]t is a short step from there to the assumption that the solution is to reduce the proportion of poor people, rather than to address structural inequalities or inject additional resources to provide the services that people need” (ibid.). On a similar note, Bauder (2002: 90) cautions that “[r]esearchers should be particularly critical of neighbourhood effects because the concept lends itself as a political tool to blame inner-city communities for their own marginality…the idea of neighbourhood effects provides scientific legitimacy to neighbourhood stereotypes…and justifies slum-clearance and acculturation policies”. Narratives of ‘neighbourhood effects’ and ‘concentrated poverty’ have been criticized for perpetuating individual-level explanations for poverty and obscuring the structural forces that cause inequality (Bauder, 2002; Venkatesh, 2003). Wacquant (2008: 284) argues that the ‘thematics of neighbourhood effects’ “conveys a falsely depoliticized vision of urban inequality, in which spatial processes appear self-evident, self-generated, or left unexplained when in reality they track the extent to which the state works or fails to equalize basic life conditions and strategies across places”. He insists that ‘effects of place’ are essentially “effects of state projected onto the city” (ibid.: 6). He further writes that “[t]o forget that urban space is a historical and political construction in the strong sense of the term is to risk (mis)taking for ‘neighbourhood effects’ what is nothing more than the spatial retranslation of economic and social differences” (ibid.: 9, emphasis in original). Venkatesh (2003: 1070), in his discussion of ethnographic neighbourhood studies, makes a similar point: “adherents to Wilson’s concept of the socially isolated urban poor, particularly ethnographers, have paid scant attention to the ways in which the state is a constitutive actor in shaping social experience”. He suggests widening “the potential field of empirical agents whose action might be relevant when making sense of any localized social practice” (ibid.). Although individuals may react to opportunities and constraints in their local environment, their social experiences are also shaped by processes far beyond the neighbourhood setting. The social processes and relations that we study in neighbourhoods also interact with non-neighbourhood factors; they are not entirely local. A recent article by Amin (2007) develops this point, and could be seen as a basis for how neighbourhood effects researchers might begin to approach the study of neighbourhood inequalities differently. Some of the limitations in the neighbourhood effects literature appear to stem from how we often view

The social mix debate and neighbourhood effects 147 the neighbourhood, i.e. our spatial ontology of neighbourhood. Although we may artificially enclose or bound the neighbourhood for research purposes, neighbourhoods are obviously not fixed containers for social action, but have far- reaching connections to other spaces and processes. Amin (2007: 105) argues that the spatial ontology underlying much urban poverty research, which sees cities (and we would also include neighbourhoods) as “as bounded spaces with distinctive markings of inequality – has allowed policy communities to get away with thinking of urban inequality as a local problem requiring local solutions”. He asserts that analysis of urban inequality cannot leave out a concern for trans- locale forces; social inequality must be regarded as the product of “multiple geographies of reward and retribution…proximate and remote” (ibid.: 105-106). Neighbourhood effects research often takes a narrow view of the neighbourhood, divorcing it from its history, surrounding context and position in the broader metropolitan structure (Wacquant, 2008). In quantitative studies, the neighbourhood is typically viewed at one point in time and as a fixed entity. Neighbourhoods are essentially transformed into “an empirical aggregate of variables” (Gotham, 2003: 727), and in the process of quantification, much information is lost. Describing the field of neighbourhood effects research, Lupton and Tunstall (2008: 114) write:

Most typically, in such research, the characteristic of neighbourhood that is described is how many poor people live there, because this is what is available to measure. Place factors such as lack of community resources or poor neighbourhood environments, and structural factors such as de-industrialisation or racial or postcode discrimination, cannot be included in these models. ‘Neighbourhood effects’ thus tend to be spoken of as ‘people effects’: out-of-work role models; anti-social peer groups; lack of bridging social capital; lack of resources to support neighbourhood shops and so on, implying that it is the characteristics and interactions of the poor themselves that account for limited individual outcomes in areas of concentrated poverty…

Thus, there are clear shortcomings and even potential dangers of the neighbourhood effects discourse. The most enthusiastic supporters and the harshest critics of neighbourhood effects research would likely agree that the neighbourhood does matter, just as geography matters, but that most of the neighbourhood effects found are, quantitatively speaking, small. Our own research does point to the existence of neighbourhood effects on such outcomes as youth education (Sykes and Kuyper, 2009) and average earnings (Musterd et al., 2008). However, it is

148 Chapter 5 important to keep in mind that quantifying the impact of one’s neighbourhood is an extremely difficult if not impossible task; the relationships between people and place are complex, and the dominant approaches to neighbourhood effects analysis do not fully account for this complexity, in particular, the reciprocality among people, space and place (cf. Smith and Easterlow, 2005) and as noted above, the importance of factors beyond the neighbourhood. Despite these complexities and much criticism, substantial effort continues to be directed at researching neighbourhood effects. There certainly are important reasons to take spatial inequalities and the relationship between place of residence and social outcomes seriously. And, despite the shortcomings outlined above, the intention of most neighbourhood effects researchers is to contribute knowledge and research that will help, not harm, those living in low-income neighbourhoods. How then, can we better research the impact of spatial inequalities and the social problems that surface in neighbourhoods? The social mix debate underscores the need for neighbourhood researchers to more fully recognize the web of connections that reach beyond the neighbourhood – the role of the state, political action and non-neighbourhood factors in interacting with and impinging on neighbourhood conditions and the experiences of residents. There is also a need to incorporate more comprehensive measures of individual and neighbourhood wellbeing into neighbourhood research and policy. Restructuring programmes that entail involuntary relocation or radical neighbourhood remodelling have been criticized for undervaluing people’s local ties, placed-based support networks, and the attachment or belonging they may feel to their neighbourhood, local school or home (Goetz, 2010). Likewise, neighbourhood effects research often takes a limited and partial view of individuals’ wellbeing. Peoples’ income levels, rates of school drop-out or unemployment – which are common outcomes in neighbourhood effects studies – tell a limited and perhaps misleading story about their quality of life. Bauder (2002: 86) points out that neighbourhood effects research is often applied to “ambiguous behavioural outcomes” such as unwed pregnancy, labour market performance, school dropout and welfare receipt, assuming that certain social and behaviour traits are “inherently pathological and indicate social dysfunction”, while they might be perfectly acceptable by some communities’ or families’ standards or be rational choices given certain circumstances. As he asserts, “childrearing ideologies, the meaning of motherhood, standards of ‘making it’ and perceptions of what constitutes good and bad jobs differ between neighbourhoods…” (ibid.: 89). Research has done much to discredit the notion that poor neighbourhoods are ‘socially disorganized’ places where the inhabitants live in a ‘culture of poverty’ or are cut off from ‘mainstream’ values

The social mix debate and neighbourhood effects 149 (see Wacquant, 1997; Gotham, 2003). However, there is still a tendency to gloss over the diversity of experiences within neighbourhoods, to centre attention on behaviour which diverges most from so-called middle-class standards, and to overlook or play down the way neighbourhoods not only constrain but also enable social action. In sum, research designs would benefit from more theoretically informed notions of neighbourhood and neighbourhood processes, which include the role of trans-local and structural factors in impinging on the neighbourhood and its residents, and would avoid an over-reliance on proxying processes and evaluating outcomes that may actually say very little about people’s wellbeing. Taking a more holistic view of the neighbourhood and the factors that constitute and shape it will further our knowledge about the meaning and source of neighbourhood effects and provide less empirical weight to policy discourse which links both social problems in poor neighbourhoods and their solution to the local population composition.

5.6 Conclusions In this paper we have outlined how the neighbourhood and its composition has taken on a new meaning in current policy approaches that aim to ‘rebalance’, ‘mix’ and ‘break up’ the composition of low-income neighbourhoods. Neighbourhoods and their respective tenure and population composition are seen as causal or contributing factors for a range of social problems, and thus ‘solutions’ to these problems also take a neighbourhood focus. The existing critiques of social mixing provide many reasons to be wary of social mixing initiatives, especially as a policy tool to help the poor. Although social mix is promoted under a policy agenda of ‘social inclusion’, mix initiatives contribute to social exclusion both in their discourse (e.g. stereotyping poor people and places) and in practice (e.g. planning restrictions, tenant screening measures, demolition of social housing). However, this policy discourse is not without a relationship to trends in scholarly research, which have placed a strong emphasis on the ‘negative effects’ that poor neighbourhoods may have on their inhabitants. As a number of commentators have pointed out, both these research approaches and current neighbourhood mix policies tend to overlook or obscure some important features of neighbourhoods: their macrostructural determinants, the function they perform for different people and the wider urban system, their historical

150 Chapter 5 and political context, how they are constructed (who comes to live there and why?), and their relationship to the policies and actions of the state. Thus, too much weight is placed on the neighbourhood as a generator of problems and as the appropriate target for policy solutions. While reconsidering many of the conceptualizations in neighbourhood research and working towards advancing theory building will not automatically lead to better neighbourhood policy, or curb the political support for social mixing initiatives, it may help to discredit some of the dominant assumptions in the policy (and scholarly) discourse, and contribute to a better theoretical basis for research and policy. There clearly is still a role for neighbourhood effect researchers, but new approaches are needed.

References

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152 Chapter 5 Rotterdam’, International Journal of Urban and Venkatesh, S.A. (2003) ‘Whither the ‘Socially Regional Research, 34(4), in press. Isolated’ City?’, Ethnic and Racial Studies, 26(6): 1058-72. van Ham, M. and Manley, D. (2010) ‘The Effect of Neighbourhood Housing Tenure Mix on Labour Wacquant, L.J.D. (1997) ‘Three Pernicious Market Outcomes: A Longitudinal Investigation Premises in the Study of the American Ghetto’, of Neighbourhood Effects’, Journal of Economic International Journal of Urban and Regional Geography, 10(2): 257-82. Research, 21(2): 341-53. van Gent, W.P.C., Musterd, S. and Ostendorf, Wacquant, L.J.D. (2008) ‘Urban Outcasts: A W.J.M. (2009) ‘Bridging the Social Divide? Comparative Sociology of Advanced Marginal- Reflections on Current Dutch Neighbourhood ity’. Cambridge, UK: Polity Press. Policy’, Journal of Housing and the Built Environ- Wilson, W.J. (1987) ‘The Truly Disadvantaged’. ment: 1-12. Chicago: University of Chicago Press. 6 One-sided geographies? The interplay among youth, neighbourhoods and schools Abstract

This paper draws on the literature and a small-scale study of youth in Amsterdam to explore some of the conceptual and methodological challenges in researching and measuring ‘neighbourhood effects’ on young people. I argue for a shift in attention from focusing on direct and independent effects of neighbourhoods, to taking into account the reciprocal relationships between people and place and the multiple and varied neighbourhoods that many youth inhabit and spend time in. I suggest that neighbourhood effects research could better link up with the geographical literature of place and space. Linking up with this literature would compel neighbourhood effect researchers to ask not only how neighbourhoods influence young people, but also how young people influence and interact with neighbourhoods, including how they come to be in particular neighbourhoods, and how they interpret, imagine, draw on and give meaning to these places. To throw light on these issues, I examine youths’ residential histories, how they interpret the boundaries and structure of their neighbourhoods, and how youth are active in shaping their encounters with place, including their role in choosing their secondary schools.

A shorter version of this chapter has been submitted for review.

156 Chapter 6 6.1 Introduction The notion that neighbourhoods have effects on the social outcomes of the children and youth that inhabit them has been a powerful one in social science research, urban policymaking, and everyday life, for instance, in the residential decisions of families in search of a ‘good’ place to raise children. A significant part of the scholarly interest in the impact of neighbourhoods on young people has taken the form of neighbourhood effects (or area effects) research. This field of research is concerned with how much and in which ways neighbourhoods matter for individual educational, health and behavioural outcomes (see Leventhal et al., 2009; Sampson et al., 2002; Small and Newman, 2001). Despite this long-standing interest, there remain significant challenges to understanding the meaning and role of the neighbourhood in young peoples’ everyday lives and longer term social outcomes. While some of these challenges stem from the methodological difficulties inherent in trying to determine the influence of complex social contexts, they also include conceptual issues concerning the definition and interpretation of ‘neighbourhood’ and the conceptualization of the relationships between people and place. In this paper, I focus on how we view and research neighbourhoods and especially how we view their relationships with, and effects on, young people. I argue that neighbourhood effects research would benefit from better linking up with the (mainly geographical) literature on place and space. Linking up with this literature would compel us to ask not only how neighbourhoods influence individuals, but also how individuals influence and interact with neighbourhoods – that is, how individuals come to be in particular neighbourhoods, and how they interpret, shape, draw on and give meaning to these places. I argue that the neighbourhood effects framework could be enriched by thinking more explicitly in terms of overlapping and reciprocal relationships running between (multiple) neighbourhood places, places of education (e.g. schools) and young people, with these relationships embedded in a wider system of institutional and social practices. Drawing on the literature and a small-scale qualitative study of youth in Amsterdam, I highlight three interrelated issues in the study of neighbourhoods and young people: the multiplicity of neighbourhoods and neighbourhood places; how the school fits into the schema of ‘neighbourhood effects’; and the mutual relationships between people and place, including how youth are selected and sorted into neighbourhoods and schools and how they are active agents in shaping their encounters with these places.

One-sided geographies? 157 Neighbourhoods and young people: 6.2 Simultaneity, selection and other caveats Research and policy interest in neighbourhood influences on young people exploded over the last two decades in the US (Ellen and Turner, 1997; Jencks and Mayer, 1990; Leventhal and Brooks-Gunn, 2000), Western Europe (Garner and Raudenbush, 1991; Kauppinen, 2007; McCulloch and Joshi, 2001; Oberwittler, 2007; Sykes and Kuyper, 2009) and elsewhere (e.g. Oliver et al., 2007; Oreopoulos, 2003; Overman, 2002). This reinvigorated interest was spurred in large part by the work of scholars, most notably Wilson (1987), on the social consequences of concentrated urban poverty. One of the main thrusts behind this work has been the notion that young people face more risks and constraints for social mobility in poor neighbourhoods than in economically better-off areas, due to such factors as peer influences, stigmatization by institutional, state or market actors, role modelling, social norms, the presence, quality and accessibility of institutions and public services, and levels of crime and safety (Leventhal and Brooks-Gunn, 2000; Sampson, 2008). While qualitative and quantitative research has demonstrated multiple ways in which the neighbourhood has meaning for people’s social outcomes, the framework of neighbourhood effects has not been without criticism (see Bauder, 2002; Gotham, 2003; Lupton, 2003; Lupton and Fuller, 2009; Martin, 2003; Venkatesh, 2003; Wacquant, 2008). Concerns have been raised over the narrow view and potentially damaging effects of the neighbourhood effects discourse and the urban policies this discourse might support (cf. Bauder, 2002; Fallov, 2010; Lupton, 2003; Lupton and Tunstall, 2008; Venkatesh, 2003). Much of neighbourhood effects discourse emphasizes the ‘negative effects’ of living amongst the poor due to presumably bad role models, a lack of conventional norms and values, and deviant work ethics, and thus focuses on presumed deficits and pathologies (cf. Bauder, 2002; Lupton and Tunstall, 2008). There is a risk that too much responsibility is assigned to neighbourhood composition – and thus to neighbourhood residents – at the expense of neglecting wider structural inequalities (ibid.; Venkatesh, 2003; Wacquant, 2008). Other issues raised include the lack of attention given to relational geographies, space and the specificities of place. Despite frequent use of spatial concepts (neighbourhood, segregation, place) and spatial metaphors (white flight, concentration effects, place effects), it has been recognized that space and spatial considerations are often neglected in neighbourhood effects research (Gans, 2002; Gotham, 2003; Martin, 2003). It is anticipated that neighbourhoods offer differing social opportunities and life chances (e.g. some present more

158 Chapter 6 ‘risks’ or offer more ‘opportunities’ than others), but how neighbourhoods and their social structures are produced and maintained, is, to a large extent, taken as given. Wacquant (2008: 284) asserts that the ‘thematics of neighbourhood effects’ “conveys a falsely depoliticised vision of urban inequality, in which spatial processes appear self-evident, self-generated, or left unexplained…”. Gans (2002) points out that the operational definition of ‘neighbourhood’ used in research is not always specified or justified. He remarks that “[a]lthough neighborhood effects researchers are working with a spatial concept, they do not always define neighborhood or report who and what in the neighborhood actually produces effects” (ibid.: 334). Commenting on the neighbourhood definitions used in quantitative neighbourhood effects research, Lupton (2003) writes:

[t]he reduced versions of neighbourhood that are used in practice hardly do justice to the understanding built up through qualitative work, and in many ways represent a backward step, defining neighbourhoods as poor or non-poor, with fixed boundaries, and with similar impacts for individuals regardless of who they are and how they are connected. While some reductionism is, of course, inevitable for quantitative work, it should not be accepted uncritically, especially if the result is that policy is founded on weak results.

Another challenge, and one of the main concerns of this paper, is that the framework of neighbourhood effects does not adequately capture the reciprocal relationships between neighbourhoods and the people that inhabit, and in turn, shape them. Although the neighbourhood is seen to affect individuals, how individuals shape the neighbourhood tends to be given little attention (cf. Furstenberg and Hughes, 1997; Gans, 2002; Gotham, 2003; Lupton, 2003; Smith and Easterlow, 2005). The idea of a neighbourhood effect conveys a mainly one-way relationship between ‘place’ and ‘individual’, even though many of the proposed channels through which the neighbourhood is thought to affect individuals involve mutual interactions between individuals and neighbourhood residents, institutions and other neighbourhood features. As Smith and Easterlow (2005: 176) remark, commenting on the field of neighbourhood effects and health inequalities, much of this research stops short of embracing the mutuality between people and place, the fact that “people make places, just as places make people”. Thus, they argue that this field of research has produced “a strangely one-sided geography” (ibid.). This issue is widely acknowledged in the neighbourhood effects literature (e.g. Buck, 2001; Leventhal and Brooks-Gunn, 2000; Sampson et al., 2002),

One-sided geographies? 159 yet still tends to be underappreciated. In their review of neighbourhood effect studies on children and youth, Leventhal and Brooks-Gunn (2000) explain that “in studying context, an important issue is the simultaneity problem, as addressed by transactional models of human development. Interactions between children and families are bidirectional in nature (Sameroff & Chandler, 1975). Those between families and neighborhoods may be as well”. Likewise, discussing challenges in neighbourhood effects research, Buck (2001: 2256) writes that “[t]he problem is in effect one of simultaneity. People are influenced by their context, and at the same time, influence that context”. Thus, as Lupton (2003) asserts, “there needs to be some mechanism for reflecting the interactions between people and place, in order not to identify neighbourhood effects that really arise from individuals, or vice versa”. The mutual relationships between people and place are a fundamental fact of human life and of substantive interest in some fields of study – people, place and space are always reciprocally interrelated (Massey, 1994). While this mutuality does indeed pose a significant challenge to measuring the ‘effects of neighbourhoods’, it suggests that we might look at the question of neighbourhood effects from a different perspective: not only how neighbourhoods affect people, but also how people affect neighbourhoods (including how they choose, are selected into, excluded from, shape and interact with neighbourhoods). To this end, Smith and Easterlow (2005) offer the complementary approach of compositional geographies, which turns the question of neighbourhood effects on its head and explores how the personal circumstances and outcomes we research (health, in their case) shape residential careers and the geographies of everyday life. Based on qualitative research, they show how peoples’ health histories and conditions influence their neighbourhood and residential careers, and thus, that health itself is drawn into the structuring of society, space and place. As they assert, “health histories and conditions are powerfully entangled with people’s trajectories into, within and out of, different spaces and places” (ibid.: 185). Although specifically dealing with neighbourhood effects on health, their comments ring true for neighbourhood effects research more broadly (cf. Hanson Thiem, 2009, for a discussion on education). These comments touch upon two important and related issues in the study of neighbourhood effects; first, as mentioned above, the often-neglected mutual interactions between people and place, and second, the well-known issue of ‘selection effects’ (or ‘selection bias’), which refers to the fact that people are not sorted randomly into neighbourhoods (or schools or other social contexts). As Sampson et al. (2002) assert, “the issue of selection bias is probably the biggest challenge facing neighborhood-level research. How do we know that

160 Chapter 6 the area differences in any outcome of interest, such as adolescent delinquency, are the result of neighborhood factors rather than the differential selection of adolescents or their families into certain neighborhoods?”. Although most neighbourhood and school effects researchers acknowledge that individuals are not sorted randomly into these places, such selection is often treated as a statistical nuisance rather than a fundamental social process and something of substantive interest (but see Doff, 2010; Sampson, 2008; Smith and Easterlow, 2005). It is exactly this ‘non-randomness’ and unequal access to and selection of neighbourhoods and schools that underlies much of the research on school choice and admissions (Ball et al., 1996; Saportio and Lareau, 1999), residential choice and mobility (Croft, 2004; Mulder, 2007; Zorlu and Latten, 2009), gentrification and discriminatory institutional practices such as redlining (Aalbers, 2005), and other gatekeeping practices that help to allocate and determine who has access to valuable urban resources and facilities (Noreisch, 2007). Selection into neighbourhoods and schools is far from arbitrary and this is of substantial importance for how we understand and research the meaning of these places. Taken together, the comments above encourage neighbourhood effects researchers to broaden the lens through which neighbourhoods and their relationships with people are viewed, and to examine both sides of the person– place relationship. In the case of young people, as I hope to show below, this means acknowledging that there are multiple neighbourhood places that they frequent, and that they are actively engaged in discovering and interacting with these places. They make decisions, some more constrained than others, about where, how and with whom they spend time, and these decisions in turn shape their experiences and interactions with – and the potential effects of – their neighbourhoods.

6.3 The current study and research context The data presented in this paper are part of a larger doctoral research project (Sykes, 2009; Sykes and Kuyper 2009; Sykes and Musterd, in press), which uses a longitudinal Dutch study of secondary education to investigate the associations between the educational outcomes of around 18,000 youth in the Netherlands and the social composition of their neighbourhoods and schools. In this paper, I draw on in-depth interviews that were carried out in November and December 2009 with 16 youth who grew up and currently live in Amsterdam (ages ranged from 18-24 years, the median age was 21 years).

One-sided geographies? 161 The interviews were semi-structured and dealt with the themes of residential history, school career and school choice, recreational activities and friendships, and home life. Through narratives and maps, the youths chronologically described their residential and school careers – for example, where they lived while growing up, how many times they moved, which schools they attended, why they attended particular schools or avoided others, and what role they played in choosing their secondary schools. Their primary and secondary schools were mapped in relation to their places of residence. They explained and often drew what they considered to be their neighbourhood and how this changed (or not) as they grew older, places they liked to go to or avoided, their spatial range as children and teenagers, their routes to school every day, and where, how and with whom they spent time in their neighbourhood and the wider city. They explained where they knew their friends from during primary school, secondary school and today – to what extent did these friends come from the neighbourhood and school and did this change over time? They were asked to evaluate their neighbourhoods and schools – for example, what did they feel were good and bad aspects of these places? How would they describe the neighbourhood to someone who had not been there before? How did they think their neighbourhood and school were viewed by others? Respondents were recruited through posters, email lists and flyers at local colleges, universities and community centres. All interested respondents replied to me by telephone or email to express their interest in the interview and 18 youth who varied in gender, ethnic and educational background and neighbourhoods of residence were selected. A time, date and place for the interview were mutually agreed upon. Two of the interviews did not occur due to cancellation on the part of the respondents and a lack of interest in rescheduling. All of the respondents were given the option of carrying out the interview in Dutch or English; for the nine who specified no preference between the two languages, I carried out the interview in English; the remaining interviews were carried out in Dutch by two research assistants, who carried out four and three interviews each. The three interviewers were females in their mid-20s. All respondents were given a €15 gift certificate in appreciation for their time. The interviews lasted between 1 and 2.5 hours and were recorded and transcribed in full. The transcripts were later coded to establish patterns around the themes presented above (e.g. neighbourhood history, school choice, friendships) and a number of sub-themes. All names of youth in this paper are pseudonyms. The 16 youth interviewed had diverse social, ethnic, residential and educational backgrounds. Because this is a small sample, I do not attempt to draw patterns in the paper in terms of youths’ backgrounds, but I give a brief description here.

162 Chapter 6 Half of the youth were second-generation migrants with one or both parents born in Morocco, Turkey, Suriname, India, Egypt, Italy and Indonesia; both parents of the remaining eight youth were born in the Netherlands. When I refer to youths’ ethnic backgrounds in this paper I state, for example, ‘Turkish- Dutch’ or ‘Moroccan-Dutch’ for the second-generation immigrant youth, and ‘native Dutch’ for the youth born to two native Dutch parents. As gauged by their parents’ levels of education, occupations, employment status and youths’ self-descriptions, just over half had a low-income or working-class background and the remaining youth had a lower-middle- or middle-class background. Four youth completed the highest ‘Vwo’ track of secondary school, nine completed the medium ‘Havo’ track, and three completed the lowest track, ‘Vmbo’ (these school tracks are described below). Amsterdam has a population of 756,000 inhabitants. Around half of the residents were born abroad or have one parent who was born abroad and are referred to in official Dutch statistics and in the public realm asallochtonen 1. The share of young people (under 20 years) with an immigrant background is higher, at around 63 percent (Dienst O&S, 2010). The largest minority ethnic groups are Moroccans, Surinamese and Turkish. The youth interviewed for this paper lived in a variety of relatively low-income and medium-income neighbourhoods in four city districts of Amsterdam: Noord (n = 3), Zuidoost (n = 2), Oost (n = 3), and Nieuw-West (n = 8). These district names correspond in English to North, Southeast, East and New-West respectively, and are used throughout the paper. In addition to these four districts, reference is made in this paper to the other districts that make up Amsterdam, namely, Centrum (Centre), Oud-Zuid/Zuid (Old-South/South), and West2. While most neighbourhoods in Amsterdam can be described as ‘mixed income’ due to the moderate overall levels of socio-spatial segregation and the nature of the housing stock3, there are relatively low-income and stigmatized areas and government programmes to reduce segregation and promote greater levels of neighbourhood income mixing (Latten, 2005; Musterd and Ostendorf, 2008). Six of the youth interviewed grew up and currently live in neighbourhoods

1 Allochtonen and its opposite autochtonen (autochthonous in English) are terms widely used in the Netherlands to signify ‘immigrant/foreigner’ and ‘native/indigenous’, respectively. Because this status is defined by parental birthplace, the second generation is also considered to be allochtonen. In this paper, I translate allochtonen and autochtonen as ethnic minorities/immigrants and native Dutch, respectively. 2 West and Nieuw-West are two different city districts; the youth interviewed all lived in Amsterdam Nieuw-West but referred to it in the interviews simply as ‘West’. 3 Amsterdam’s housing stock consists of 50 percent social-rented housing, which has historically served a wide range of income levels. Of the 16 youth interviewed, 13 grew up in social-rented housing and three in owner-occupied housing.

One-sided geographies? 163 that have been selected as ‘priority areas’ by an area-based programme of the Dutch Ministry of Housing, Neighbourhoods and Integration programme, which aims to improve the conditions in what it sees as the 40 most socially troubled neighbourhoods in the Netherlands. Part of this paper deals with youths’ school experiences, so it is important to provide some key details of the Dutch school system. School choice is an important and widely debated issue in the Netherlands. Families are granted, in principle, open school choice, both at the primary and secondary level. There is a diverse supply of schools, including public schools run by the state and schools established on the basis of specific faiths (e.g. Catholic, Protestant, Islamic) and pedagogic principles (e.g. Montessori, Steiner), which are run by the associations or foundations that set them up. All schools, regardless of faith or orientation, receive equal status and funding from the government. Most faith-based schools (particularly the Protestant and Catholic schools) serve culturally heterogeneous populations and religion no longer plays an important role in school admissions. There are a small number of Islamic, Hindu, Orthodox Christian and Jewish schools, where religious or cultural identity does play a role; for example, in the (one) Islamic secondary school in Amsterdam, 98 percent of students have a non- Western background, and naturally it attracts Muslim students (Karsten, 1999; Karsten et al., 2006). Young people are more segregated in schools than in neighbourhoods, and family school choices and institutional features of the school system are known to reinforce this segregation (Karsten et al., 2003, 2006). As in countries such as Germany, the Netherlands has a ‘selective’ secondary school system, in which students are divided into different educational tracks, differentiated by curricula, prestige, years of duration and possible destination. There are three main tracks: vocational secondary education (Vmbo), which lasts 4 years and is further divided into four sub-tracks; senior general secondary education (Havo), which lasts 5 years; and pre-university education (Vwo), which lasts 6 years and is further divided into Gymnasium (which includes Greek and Latin languages) and Athenaeum (without classical languages). At the end of primary school, students are given a recommendation as to the most suitable secondary school track to follow based mainly on their performance on a standardized test (Cito test) and their general skills, motivation and interests, as assessed by their teachers. This recommendation is a critical factor in youths’ secondary school decisions, because not all schools offer every track. Moreover, at the schools that do offer

164 Chapter 6 multiple tracks, students’ recommended track level determines their place (i.e. their first year class type) within the school4.

Defining neighbourhood: 6.4 A multiplicity of neighbourhoods In both research and everyday life, neighbourhoods are defined and understood in numerous ways. Neighbourhoods are ‘multiply constructed’; they may be defined and named by officials, but are also defined, interpreted and imagined in multiple ways by different groups and individuals (cf. Gieryn, 2000; Martin, 2003). The flexibility and slipperiness of the neighbourhood concept and the constraints in defining and operationalizing it for empirical research are widely recognized (e.g. Gotham, 2003; Martin, 2003; Lupton, 2003). While neighbourhoods are always understood to be geographical areas, how these areas are defined in research varies depending on the research questions and topics of investigation, and often, data availability. Some studies adopt census tracks or other administrative units, others construct ‘micro-neighbourhoods’ or bespoke neighbourhoods delineated by the area encompassed within a certain radius of a respondent’s home, and others ask respondents what they perceive to be their neighbourhood and explore and compare these interpretations (e.g. Andersson and Musterd, 2010; Lee and Campbell, 1997). Individuals’ perceptions of neighbourhood and neighbourhood boundaries also vary widely. Two people living on the same street or even in the same house can have a different view of what constitutes their neighbourhood (cf. Burton and Price-Spratlen, 1999; Lee and Campbell, 1997). Moreover, one’s spatial sense of neighbourhood may expand and contract over the life course and vary depending on the activity in question (e.g. using local facilities versus greeting neighbours) (Lee, 2001). People also inhabit multiple neighbourhoods, both sequentially over their life course due to residential mobility and neighbourhood change, and for some, simultaneously. Based on their ethnographic research, Burton and Price-Spratlen (1999: 86) note that many children and youth call a multiplicity of residences their homes – “that is, they may be members of families who simultaneously co-reside across multiple households located both within and across a variety of neighbourhoods”. In their study, one third of the children simultaneously resided in 2 to 4 households across several

4 Depending on their performance, students can transfer upwards or downwards in track level, or transfer to a higher track after successfully completing a lower one, and many do so. Some schools also delay the choice of school track with a ‘transition year’ in the first year.

One-sided geographies? 165 distinct neighbourhoods, as they spent different days of the week with parents, grandparents and other carers. The 16 youth that were interviewed for this study detailed their residential and school histories. When asked what they considered to be their neighbourhood, both now and when they were growing up, their answers revealed both the flexibility of the neighbourhood construct and the multiple neighbourhoods that many had inhabited due to residential mobility. Of the 16 youth interviewed, six had what might be considered a ‘conventional’ neighbourhood and school career – attending one primary followed by one secondary school, living in one neighbourhood at a time and moving house infrequently (i.e. once during childhood) or not at all. The others had much more varied experiences. Eleven of the youth moved house at least once (and up to seven times) while growing up, with nine of these constituting moves between different (administrative) neighbourhoods, and the others within the same neighbourhood. Vincent (21 years, native Dutch) had lived in three neighbourhoods and attended four primary schools and three secondary schools. Four of the youth spent time regularly at both of their (divorced or separated) parents’ homes while growing up, which were located in different neighbourhoods. Lukas (22 years, native Dutch) had moved four times by the age of 18; he explained his residential history5:

I was born in a shared-housing community [woongroep], on the Frans Street, it’s a real nice neighbourhood. I was born there, in like a pretty big house, but of course, people have children so you have more conflicts I guess, so we moved out of that neighbourhood and then I was about, I guess five, and we moved to the Indische Buurt, it’s in Oost, it’s here (points to map), we were on the Grijze Street, it was more like, ah ghettoized, it was a big difference. Then I guess my parents had a little bit more money, but not that much more, so we went to a different neighbourhood where you could play outside, that was near Rozen Street, it’s called Zonnen Street, it’s right here (map). After that we went here (map), then when I was about 13 we went to live over here. My father still lives there. When I was 18 years old I squatted a place on the Pijp Street, so that’s here (map), close to the police station there, but only for about a year, then I lived…

5 Street names have been changed to protect the youths’ anonymity. Texts from Dutch interviews have been translated into English by the author. In the interview text, the youth often refer to ‘here’, which indicates their reference to a map during the interview.

166 Chapter 6 Residential histories not only provide interesting details in the lives of these youths, but are important when trying to understand the meaning and role of the neighbourhood in the lives of young people. As Furstenberg and Hughes (1997: 28) comment,

residential mobility is a key means by which parents choose the environment experienced by their children. Because of changes in residence, a child may be exposed to a variety of different neighborhoods while growing up. The impact of a particular community on a child will likely depend on the child’s duration of exposure to the characteristics of that community, the ages at which it occurs, and, perhaps, the types of neighborhoods that precede and follow it.

Residential mobility not only played a part in determining which neighbourhoods the interviewed youth were exposed to, and thus, the people and places they came into contact with, but also in their identity formation and subjective feelings about and attachment to their neighbourhoods and Amsterdam. For example, Lukas (above) considered almost all of Amsterdam to be his ‘home’. He had lived in several parts of the city, had been granted a lot of freedom and autonomy to travel around the city when he was growing up, and had friends “really, from all over Amsterdam”. He felt a strong attachment to Amsterdam, and even got “a bit homesick” when he went to Utrecht (a neighbouring city) briefly for college, but felt no special connection to any of the specific neighbourhoods he had lived in. In contrast, Melissa (22 years, Indonesian-Dutch) lived with her mother in one apartment in Amsterdam West for her whole life and for her, that neighbourhood “is home, like my real ‘home town’. That’s my place”. She spent time in other parts of Amsterdam, but preferred to be close to her home neighbourhood and wanted to continue living there after she moved out of her mother’s house. We were in Amsterdam Oost at the time of the interview and she explained,

I come here sometimes, but it’s not my place to be, and I don’t feel comfortable on this side of the city. This (points on the map to her neighbourhood) is really my part of the city, I like this. Here (map) is also the park and this is a big pond where we hang out. Oost is not my location. And with the bicycle at night, if I have to bike in Amsterdam Oost I feel a little bit scared because I don’t know the neighbourhood, but at the same time [of night] in my own part of the city, then I feel that it’s ok, then I’m not scared at all.

One-sided geographies? 167 Vincent lived in the same neighbourhood for fourteen years and knew “almost everyone” on his street. He explained that because he had switched schools several times (he attended four primary schools and three secondary schools), most of his friends came from outside school, in his words, “from the neighbourhood, basically the boys that were always outside”. He explained:

I went to a lot of primary schools. So actually, I never had real friends from school. I just had friends from outside school, that I knew from the street. We played together, and then when you’re 10 or 11 [years old], you go more to the street and then you get to know more boys who do that too. That’s actually how I know all of my friends until today. Since I was 12 or so.

For most youth, their neighbourhoods ‘stretched out’ as they grew older; as Matthews and Limb (1999: 72) note, “[t]he routine world of a six-year-old is no more than a ‘spatial bubble’ within the world of a young teenager”. Esther (19 years, Italian-Dutch) described her neighbourhood when she was younger: “so my neighbourhood was really this (points to map) and I was allowed to play three streets from mine, not further, so just those three streets were my neighbourhood when I was little and when I got a bit older I could go around all the places”. The respondents described their neighbourhoods during childhood as “my street”, “just in front of the door”, “my street and the street behind me”, or a larger block, usually marked by tram tracks or a busy road that formed temporary boundaries, inscribed by their parents. What Besma (19 years, Moroccan-Dutch) considered to be her neighbourhood shrunk between her childhood and teenage years. While drawing a map, she described her childhood neighbourhood in great detail: “here we had a church, then here some houses for seniors. And here an apartment building where seniors were cared for, but now it’s a hotel. And here you had a day care, with a small playground. I played there a lot, with swings and stuff. My street was here. So that was my street, and here was another street…”. When describing her neighbourhood of today, she explained, “[y]eah, now it’s just my street. Not really more”. Once she entered secondary school she spent little time in her neighbourhood because her school was located in a different district of Amsterdam and her schoolwork took up more of her time; as she explained, “then it was really just work, school and you go back home to sleep or do homework”. Some youth had adopted entirely new neighbourhoods. After explaining what she considered to be her neighbourhood in Amsterdam West, Ava (18 years,

168 Chapter 6 native Dutch) added, “but, from the moment I went to [secondary] school, at the Amsterdams Lyceum, that was really more my neighbourhood. I never really went home, and I was not at all with the children from the neighbourhood”. Although she did not live there, she considered the area of her school to be her neighbourhood because she went there almost every day for school, many of her friends lived there and she also felt “more at home” there. She had described her own neighbourhood in negative terms (“boring”, “anonymous”, “no real special features”, “really closed [people]”). As soon as she was a teenager, she preferred to spend her time in the city centre, in the Oud-Zuid neighbourhood of her school and in the neighbourhoods of her school friends. Many of the youth described their neighbourhoods in relation to what it was not and by referring to other places (“it’s poor, but not like the Bijlmer6”). Esther juxtaposes her neighbourhood with a neighbouring area that “you didn’t want to be part of”:

This (points to map) is called IJplein and that was really my neighbourhood because on the other side of the road, you got Vogelbuurt and that was really bad, that was even worse than my neighbourhood. It was, I think it was three or four years ago it was the poorest neighbourhood in all of the Netherlands. And there are children there with hunger, they don’t go to school with breakfast, so yeah, the schools give them breakfast. So you didn’t want to be part of that neighbourhood. And you know, there was always trouble, because there was this really nice playground [in the other neighbourhood] with a lot of things and we didn’t have that in our neighbourhood so we went to the other one, and they [kids from the other neighbourhood] were always fighting, and getting us girls away, and hitting us, cause we were not allowed to play there. So that’s really the worst part of the neighbourhood, so my neighbourhood was really this (points to map).

The youth were attentive to the social differences and inequalities across neighbourhood spaces and many drew on these in their descriptions. Mirak (19 years, Egyptian-Dutch) explained that his neighbourhood had “two parts”, one with social housing and another with single-detached, owner-occupied housing; “[y]ou had this area that was social rented and that area that was separate [single-detached] housing, so you had more rich people there and well less, well

6 The Bijlmer is a neighbourhood on the outskirts of Amsterdam with the most well-known housing estates in the Netherlands, infamous for its reputation of neighbourhood decline and social problems (see Aalbers, 2010).

One-sided geographies? 169 poorer people here”. He lived in the social housing part, but because he attended a primary school in the other part, he spent a lot of time and “pretty much grew up” there. He elaborated:

it [the neighbourhood] actually had two sections, the apartments, the flats, that’s where I lived, it was social rent, and the other side was separate housing and I went to primary school there…So, it’s like there are two parts. I pretty much grew up in that other part, well I lived here (map), but when I visited my friends I always went to the other part.

This division was relevant for him; as he later described the recent social problems in his neighbourhood (“it’s really going downhill”), he explained that this occurred in the “social housing part” of the neighbourhood, not the other part. The childhood friendships he maintained today were also with people from “the other part”. Melissa also referred to the type of housing in the area around her home to contrast where she lived (in social housing) to where her boyfriend lived nearby in a “good neighbourhood”:

Tim lives in a good neighbourhood. It’s also in the same area, because I live here (map) and he lives here. So it’s not far away, but these are big houses, family houses, and I live in a flat, and that’s different. And it’s quiet over there, and they have a park over there, and so it’s different…they are not far from each other, but different.

Youths’ reports of their residential histories and interpretations of neighbourhood boundaries underscore the multiple neighbourhoods that young people inhabit and the different ways in which they define these places. As Lee (2001: 33) remarks, although “we cannot fix the elastic nature of the concept, we should at least take it into account”. Several of the youth juxtaposed their ‘home neighbourhood’ with the neighbourhood of their secondary school, as apparent in Ava’s comments above, which brings up an important issue: how does the school fit into the schema of neighbourhood effects? And vice versa, how does the neighbourhood fit into the notion of school effects?

170 Chapter 6 Neighbourhoods and schools: 6.5 Interconnected places Children and youth allocate much of their time between their neighbourhoods and schools and these places overlap as places of learning, socialization and where friendships are made. As Karsten (2010) points out, schools and neighbourhoods are among the most important places where young people have the opportunity to extend their social networks. She suggests that the “relationship between children’s social networks at school and in the neighbourhood is seriously under- researched. Do children develop school friendships after school by inviting schoolmates into their neighbourhood play groups and do children get to know neighbourhood children without attending the same school?” (ibid.: 4). In the interviews, several youth referred to their “neighbourhood friends” and their “school friends”. As one youth explained, “I’ve got a couple groups of friends. So, like one group is from my high school and we’re still together, and one group is from my hobbies, and one group is from the neighbourhood. And they’re not mixed”. The connections between youths’ neighbourhoods and schools also have implications for youths’ spatial ranges and familiarity and understanding of the social and spatial realm. Lukas explained where he knew his friends from when he was younger and how this changed when he entered a secondary school that was located in a different “more high-class” neighbourhood:

Most of my friends were from around [me], a bit from Oost and close to the centre. Of course there were different types of people, some were more rich and some more poor, it was really different. I had more friends from the neighbourhood who were also not that rich, and it really changed when I went to the Montessori Lyceum, because it’s a bit like, the cultural elite is at that school, so a lot of people are quite wealthy there, but some people aren’t of course. This [his neighbourhood] was more lower-class and this [the neighbourhood of his school] was more high-class and it’s a different culture, so when I went on my bike from here to here (map), cause first I still lived there when I started at that school, you saw the difference in the cars and the people and it got nicer.

Esther grew up in a low-income neighbourhood in Amsterdam Noord, but attended the same Montessori Lyceum as Lukas, in the Oud-Zuid neighbourhood of Amsterdam. She also commented on her experience going to that school:

One-sided geographies? 171 In high school I had these friends and they grew up in the grachtengordel7 and they were real chic, they were real different people, they spoke differently, I had this slang from the street and they didn’t. So yeah, it was different and they didn’t grow up with different cultures, so until I was 12, I had one Dutch friend and that was it and the rest were all mixed from all different kinds of countries, but not the Netherlands.

Mirak explained that attending a high school closer to the centre of Amsterdam meant that he now had friends from that part of the city, and thus spent less time in his home neighbourhood in Amsterdam Zuidoost: “well in the last three years, I pretty much go to the city for everything that I do, because all the friends I got to know from high school and their friends, that’s pretty much my friend group right now, and they live scattered around the centre...So I don’t stay in my neighbourhood, only to sleep and eat”. Thirteen of the youth attended a primary school in their (immediate) neighbourhood, located between a three and ten minute walk away. These youth travelled to primary school on foot, and when they were older, also by bicycle. The other three youth attended the closest primary school to their house, but which was located somewhat further away (approximately 25 minutes by foot). At the secondary school level, the distance between home and school was much larger. Many did not have a suitable school in their home neighbourhood, and thus had to leave their neighbourhood to attend school. Others preferred to attend a school in another neighbourhood, despite having a school closer by, because it offered a special focus or feature; special school characteristics that the youth mentioned included Montessori education, Gymnasium, Spanish language classes, Islamic education, and multiple school tracks at the same school. Several of the youths explained how they and their neighbourhood and primary school friends went in different directions once they entered secondary school, because they made different school choices and had different track recommendations. Melissa had always walked to primary school with four girls from her street. She explained that in secondary school “it changed, because everybody has a different recommendation, someone has Vmbo, Havo, Vwo… So then it changed, and then it changed the friendships also”. The majority of schools offer multiple tracks, thus, internal or within-school segregation also exists, due to the large differences in students’ social and ethnic backgrounds across the different tracks. Students with a low socioeconomic

7 The grachtengordel (canal belt) of Amsterdam refers to the streets along the canals in the city centre, which are among the most affluent areas in the city.

172 Chapter 6 status and from minority ethnic backgrounds are over-represented, on average, in the lower tracks and under-represented in the higher tracks (Herweijer, 2009). In the interviews, I was interested in whether the youth had friends from different school tracks, and their answers suggest that school tracking does reinforce same-track friendships and within-school segregation, as has been found in other studies (cf. Hattie, 2002; Schofield, 2006). Mirak attended the highest secondary school track, called Gymnasium, at a school which offered multiple tracks; he recalled that “Gymnasium felt like a separate part of the school, we didn’t really mix with the others”. When asked whether he had friends who did a different level than him in secondary school, Louis (24 years, Antillean-Surinamese-Dutch), a Mavo8 student, explained:

Yeah, usually you hang out with your own level. Because people at the Gymnasium, I didn’t know them, I saw them, but they weren’t my friends. We didn’t really hang out together, it’s like those people, they look for each other, you know. And I think there’s also a different mentality, like, you know, they rather go home and study or they go in the library of the school and study over there. And people from Mavo, I mean I don’t say that they are not smart, but they have different interests, you know.

In neighbourhood effects research, the school is sometimes implicitly thought of as (part of) ‘the neighbourhood’ (e.g. Ainsworth, 2002), while in other studies it is contrasted with the neighbourhood. The interviews demonstrate these as two important, but often very different, social environments for youth. Entering secondary school usually meant a new peer group, a new neighbourhood and a new marker of identity (e.g. being a ‘Gymnasium’ or ‘Vmbo’ student). Mirak grew up in the Zuidoost of Amsterdam in a low-income neighbourhood and attended the same school as his older brother closer to the city centre, but they attended different tracks within the school. I asked him to explain the backgrounds of his friends to me:

Well, because I went to Gymnasium at high school my friends were pretty much white, and high educated and their parents were pretty rich and stuff. I had a few friends that were from another ethnic background and I don’t really see them anymore, but the people I

8 In the school year 1999/2000, ‘Mavo’ was merged with another track into what is now called ‘Vmbo’; Louis began school before this merger.

One-sided geographies? 173 do see from my time in high school are really in the upper, upper class, you know, because they were from Gymnasium, well actually that doesn’t mean from what background you are, but it did actually. It is related, and so, my friends are pretty much all white, but when I look at my brother who went to Havo at the same high school he has a lot of mixed friends. So it’s really funny because, because I did Gymnasium I have all these friends that are from rich families and because my brother did Havo he has a really mixed friend group… It made me more white than my brothers, having done Gymnasium, because of the way I talk, it’s more like higher, and my brother’s more ghetto, like street talk…

Thinking about youth situated in school tracks, schools, and neighbourhoods, which are dynamic (e.g. youth switch schools and move house) and overlapping, reveals some of the complexity that comes with trying to measure the effects of neighbourhoods and other social settings. Young people’s geographies are complex, and while the neighbourhood may be an important place in their everyday experiences and longer term development, they have a wider range of socio-spatial experiences, which are also shaped by, and in turn shape, their neighbourhood experiences. My aim is not to suggest that neighbourhood researchers should try to capture this entire web of social and spatial connections, but rather to highlight some of the ways in which a consciousness of these connections affects the way in which we think about neighbourhood effects, and young people’s experiences in neighbourhoods. In the next section, I consider how young people shape their orientation towards their neighbourhoods and schools.

6.6 Choosing places As outlined above, considering how youth are selected into neighbourhoods and schools has importance for understanding the effects of these places. Writing from the US, Duncan and Raudenbush (1999: 36-37) explain:

The contexts in which children develop are not allocated by a random process…A child’s immediate neighborhood and, to a somewhat smaller extent, schools also have an element of parental choice. The propensity of individuals to choose higher or lower quality child care

174 Chapter 6 or to move to better or worse neighborhoods or schools depends on background characteristics and current circumstances…substantial effort is required to model these propensities as a precondition to drawing conclusions regarding the causal nature of context influences.

If we want to understand the influence of place, we ought to explore how places and their geographies are produced and how people are sorted and sifted across place. This would include looking at the choices and constraints surrounding residential careers and school choice decisions, and would also include young people’s voices. While youths’ parents clearly are the primary people engaged in residential decisions, youth typically play quite a large role in deciding which secondary schools they attend and they can (purposefully or non-purposefully) shape how oriented they are towards their school and neighbourhood settings, through their decisions and actions concerning the friendships they maintain, their activities, the places they visit and hang out in, and so on. While youth and their families can and do make these kind of decisions, they result from the interaction of preferences, constraints and opportunities. Schools and neighbourhoods, and the places within them, are not equally accessible to everyone. There are many reasons to stretch the notion of selection effects beyond just a parental decision and the choice of residence – as often is the case in neighbourhood effects research – and to consider young people’s role in the selection of schools and other places. The selection of these different places are related (e.g. residential decisions affect school choice decisions), but also, the selection of and orientation towards one place impacts upon the selection of and experiences in another place. For example, in Ava’s comments above, her school neighbourhood became her ‘home neighbourhood’, as she preferred this place over her (residential) home neighbourhood and most of the friends she made at school lived there. Oberwittler’s (2007) study of neighbourhood effects and youth in two German cities offers an empirical example. He found that the spatial location of youths’ schools in relation to their home neighbourhoods had a relationship with the spatial distribution of their friendship circles. As would be expected, youth attending schools further away from their home had a greater proportion of friends from outside their neighbourhood than their counterparts who attended neighbourhood schools. He suggests that any kind of ‘neighbourhood effect’ is thus likely to be contingent on the spatial orientation of youths’ peer groups and their routine activities, and his results of neighbourhood effects on youth delinquency appear to support this view. As he correctly points out, this kind of finding highlights how the impact of people’s social contexts involves an element of self-selection, which encompasses more than just the

One-sided geographies? 175 initial selection of a context (e.g. residential choice), but also that which shapes peoples’ embeddedness in and exposure to their neighbourhood, such as where and with whom they spend time and where they attend school. Young peoples’ ‘choice’ of place is guided and constrained by a number of factors, including access to money and transport and the rules laid down by their parents and other adults who control space (e.g. through curfews, policing, legal ages of entry into establishments and other spatial restrictions on the basis of age) (cf. Valentine, 2003). Peoples’ spatial range and the experiences of inhabiting places are known to be shaped by factors such as gender, age and social class (Reay and Lacey, 2000b; Massey, 1994; Mathews and Limb, 1999; Valentine, 1997). Work in the field of children’s geography has shown that girls tend to be granted less autonomy and territorial mobility than boys and that their outdoor behaviour is subject to stronger parental interventions (cf. Matthews and Limb, 1999). Despite the constraints they face, studies shed light on the power young people have to discover, choose and shape the places in which they spend time (Thomas, 2005). Even small children are active in discovering, selecting and interacting with the places they come in contact with, although usually under the supervision of adults. As children get older, they become more autonomous in choosing the places they encounter. They learn how to navigate places, gaining familiarity with their surroundings and learning which places feel dangerous, safe, fun and comfortable (Thomas, 2005; Wridt, 2004). They develop affinities and aversions to places and their experiences build on past encounters with places (Hollingworth and Archer, 2010; Reay and Lucey, 2000a). The recognition of this agency adds a layer of complexity to the notion of neighbourhood effects; the effects of place are not uniform across individuals, but interact with how individuals perceive these places, their past experiences of place, and how and for what reasons they use these places. The youth interviewed played an important role in choosing the places they inhabited growing up, consciously and unconsciously, through their decisions about which secondary schools to avoid and attend, their hobbies and activities, preferences for indoor or outdoor play, decisions about how often they would live at each (separated or divorced) parents’ home, and the friendships they maintained. For example, while some youth said that they were “always outside playing” as children and knew “almost everyone” from their street, others said that they were not really “an outdoors kid” and preferred to play inside their house. Vincent commented, “I was always outside. Basically, always. From, I think from the time I was 8 years old or so, I was always outside, except to eat and sleep”. Tamir (19 years, Turkish-Dutch) was also outside a lot “playing football, catch, hide-and-seek”. Some older boys in his neighbourhood organized mini-

176 Chapter 6 football tournaments that he often participated in. Both he and Vincent knew many of their neighbours; Vincent estimated around 15 people by first and last name and Tamir estimated over 20. This was less the case for the youth who said they preferred to play inside, or for the two females who were expected by their parents to stay much closer to home and estimated that they knew about 3 neighbours. Besma played outside with other children, but recalled that her and her friends’ parents would sometimes “get anxious”: “well, then they [people in the neighbourhood] kept saying ‘there are kidnappers in the neighbourhood’ and then we had to stay in front of our house or at the back. You were kind of limited, we couldn’t go far because the parents would get anxious if we stayed away too late, too long. I didn’t really like that”. One place that many youth played a role in choosing was their secondary school. School choice research focuses almost exclusively on the choices and preferences of parents, rather than the preferences of children and youth. Reay and Lacey’s (2000b) research on the school choice perspectives of 10-11 year olds, as they were selecting and applying to secondary schools in inner-city London, shows that the children played a central role in the school decision- making process and were often seen by their parents as the ‘expert’ on the local schools. Inside and outside of school, the children also generated peer group discourses about secondary schools, in which certain schools were described as ‘popular’, ‘good’, the school ‘everybody wants to go to’, in contrast to those that were less desirable. Of the 16 youth that were interviewed for the current study, all recalled being central actors in their secondary school decision-making process, and many felt that they had had the final say in the decision. As one youth explained, “[f]or secondary school, I was free to choose. I had my own say. I discussed it with my parents. But I had my own say”. Just one of the youths felt the secondary school decision had been entirely her own, with no real input from her parents. Karima, a 22 year old Moroccan-Dutch female, moved with her family to the Netherlands from Morocco when she was an infant. She is the eldest child in her family and thus the first to navigate the Dutch school system.

Interviewer: Did your parents want you to go to a school nearby? Karima: No, that had nothing to do with it. That was my choice, I made it myself. I also had another school that was closer by, but I didn’t want to go there. Because I thought, yeah, ‘this isn’t the school that is going to motivate me’. So, I went to the other school. I just registered myself there. I did it all myself.

One-sided geographies? 177 Besma had the final say in her secondary school decision, though she sought the input of her “parents, friends and family”. After attending an Islamic primary school in her neighbourhood, she decided to attend the Islamic secondary school in Amsterdam, located in a different district. She explained how her school choice was made:

Well, actually that was my choice, because I saw that all of my friends were going there and I saw that it was an Islamic school, so I thought it must be a nice school. And yeah, based on that, I went there. And my parents also thought it was good. They were like, ‘yeah, just go, better’. When you hear stories about other schools, then I think, yeah they smoke in front of the school and so, it can have a bad influence on you. My parents thought so too, so they really stood behind me and motivated me to go there.

Tamir explained why he avoided the same secondary school, which was near his neighbourhood:

Interviewer: Were there any reasons to avoid some schools? Tamir: Yes, for example the ICA, I didn’t want to go there and my parents didn’t want me to either. Interviewer: What’s that? Tamir: That’s the Islamic College Amsterdam. That’s too much [to do] with faith and belief, really, and like faith and school should be separate, I think. Because you go there to learn and not to… [unfinished sentence].

For Ava, school choice was a means to get out of her neighbourhood on the west side of Amsterdam. She avoided a school closer to home, which her father wanted her to attend, because she wanted to be closer to the city centre and wanted “a new beginning”. She had been “teased a lot” by other children during primary school and many of them would be going to the school close to her home. She chose a secondary school in the Oud-Zuid district of Amsterdam, several city districts away from her home, in an area that she was really fond of. She commented that now, she feels “actually more at home” in Oud-Zuid than in her own neighbourhood. She explained her school choice:

178 Chapter 6 My father wanted me to go to [neighbourhood school], but then I thought that was nonsense. I wanted to go to the city, because, you know, if you are already there, then you go can go more often to the city, and I wanted to be there all the time, I don’t know why. I always went shopping with my mom in the city. And I found it much more fun than [her neighbourhood], I found that quite boring…And that [neighbourhood] school just seemed to me like nothing [special]. Because really everyone from my neighbourhood was going there. And I just wanted a kind of new start.

In secondary school, she made new friends that lived in different areas of Amsterdam and began to spend more time with them in their neighbourhoods, in the city centre and “hanging out around the school”. By the time she was in secondary school, she did not maintain any of the friendships from her neighbourhood and was “hardly ever at home”. She explained what attracted her to the school in Oud-Zuid:

It was actually on the posters up at my [primary] school and I thought it was just really nice and they also had Spanish, which I thought was very nice. And then I went there to take a look [during an open day] and I thought it was such a beautiful school and then it was basically just, I belonged at that school, period.

While youth played a role in choosing their social and spatial environments, some places also ‘chose’ them. Because students must attend a school that offers at least their recommended track, and not all schools offer every track, their track recommendation is a crucial factor in their secondary school decisions. After not meeting the test score requirements for the first school she visited, Karima later explained that she opted for another one, in large part because it offered Vmbo, which was her level. Before knowing the results of her Cito test, Suus (19 years old, Hindustani-Surinamese-Dutch), visited four secondary schools during open days. As she scored higher on the test than she had expected, two of those schools were automatically ruled out because the tracks they offered were too low for her. Youths must find a school that offers their appropriate track, but some had anticipated switching tracks in the future, and thus wanted to find a school with multiple tracks. Sabine (24 years, Hindustani-Surinamese-Dutch) explained her school choice:

One-sided geographies? 179 I made that choice myself. Of course with a little bit of help from my mother. I visited several schools. In Amsterdam Noord the choice, well I wanted the opportunity to do Mavo/Havo, and it was basically the only school that you could go from Mavo/Havo to Havo/Vwo, still in the same building. And you didn’t have that at other schools. That attracted me…and how everybody interacted, the teachers, the atmosphere.

Vincent started secondary school in Amsterdam at the Vwo level. After some problems at home he had a hard time concentrating at school: “I really couldn’t concentrate on school. It actually didn’t matter at all to me. In those two years, I actually did nothing for school”. He was then transferred to Vmbo and decided to go to a school in a small city outside of Amsterdam. He was looking for a school that offered all three educational tracks: “Then I thought, I’ll just go to Weesp, it’s pretty easy to get there...In Amsterdam there actually aren’t so many schools with Vmbo, Havo and Vwo. And there’s often a lot of immigrants [allochtonen] at those schools. I didn’t really want that, and neither did my parents”. Youth were not asked whether the ethnic character of the school was a factor in their school choice, but two mentioned that it was when recalling their school choices. For Suus it was an extra reason to attend the school, and for Vincent it was a reason to avoid the schools in Amsterdam. Suus explained that she avoided one of the schools in her neighbourhood because “it was mainly native Dutch students there and I just wanted a mixed school, and that was definitely this school [that she attended]”. She had “heard bad things” about the other school and “didn’t even go there to look at it because I had already decided that I wouldn’t go there”. She ended up choosing a school that was a 15 minute bike ride from her house and about half of the students in her classes there had a minority ethnic background. She explained that her sentiments about school mix had been shaped by her primary school experience where she was “one of the only dark kids in class” and felt “discriminated against”. Youths’ and their families’ preferences are part of the school choice process, but school factors also play a role. A number of formal (e.g. school tracking, school choice policies) and informal institutional arrangements and practices work to attract, exclude and sort students across and within schools and thus determine their place in the educational system (Bourdieu and Passeron, 1990; Warrington, 2005; Noreisch, 2007). As Schofield (2006) points out, these arrangements are so much a part of the lived experience of members of society that they are often taken for granted.

180 Chapter 6 Karsten et al. (2001) note that schools adopt strategies to improve their reputation or position in the local market, with one such strategy being to ‘regulate’ school intakes. While this is most noticeable in schools that have the official means to do so (e.g. private schools), studies also document gatekeeping practices in the public school sector (Gramberg, 1998; Noreisch, 2007; Warrington, 2005). As Noreisch (2007: 1324) writes, “[e]specially in schools in very heterogeneous neighbourhoods, ‘certain types of students become more sought after’ (Ball, 2003: 45-46)”. Karsten et al. (2003) surveyed parents in the Netherlands and interviewed the headteachers of 43 primary schools located in 11 neighbourhoods, which were pre-selected because they had schools with ethnic compositions that diverged sharply from that of the school age population in the surrounding neighbourhood. In addition to finding evidence that parental school choices reinforce school segregation, they found indications of a number of forms of gatekeeping on the part of the schools, including, “asking for a very high parental fee9, using waiting lists for certain groups of pupils, limiting the number of children who do not speak fluent Dutch…advising parents to go to another school ‘because they will probably feel more at home there,’…” (ibid.: 469). In a study highlighting the intricacies of school choice and admissions in a socially and ethnically diverse district of Berlin, Noreisch (2007) demonstrates how the school admissions system is kept ‘intentionally non-transparent’, in order to maintain flexibility. Although headteachers do not officially have the authority to decide whether an application is accepted or not, she finds that they “often cast the deciding vote” (ibid.: 1307). Based on her interviews with school officials, she comments on the admission process: “it is clear that certain exceptions are made and even here [in the interview text] it is admitted that in some cases it is necessary to please those parents who are already showing an increased interest in their child’s schooling by engaging in the application process and are therefore also likely to be involved once their child begins school” (ibid.: 1323). While the youth interviewed could not comment on how their primary schools were chosen or on the perspective of the schools, it was clear that they (and their families) had made school choices differently. Some had parents that seemed to be more directly engaged in the school choice processes than others, for example, by taking the youth to multiple secondary school open days and giving them advice on schools. One youth claimed that his father “knew someone in the school inspectorate” and thus was aware of which schools “were good”. Others, like Karima above, choose their schools mainly without parental input.

9 Although compulsory education is free in the Netherlands, some schools can ask for a parental fee for extra-curricular activities.

One-sided geographies? 181 This was not a sign that their parents did not care, rather, some of the youth explained that their parents trusted that they could make a suitable choice or wanted to give them the freedom to choose. As Lukas explained, “my mom actually tried to get me into a Gymnasium, cause she did it. But I didn’t feel like it…it was actually kinda my decision, how strange that might seem, because you’re only 12 or something, but I thought like ‘I want to go there, I definitely want to go there’, so I went there”.

6.7 Interpreting the neighbourhood Gotham (2003: 723) argues that although neighbourhood effects research places considerable importance on the significance of spatial location, it has underemphasized the meanings of space and place (see also Gans, 2002; Martin, 2003). He suggests that considering space and place in neighbourhood research would shed light on the dynamic interplay between human agency and place. In the geographical literature, space and place are understood to be mutually dependent yet distinct concepts (Agnew, 2005; Merrifield, 1993). Space can be understood as the field in which places are embedded. Space as a whole “takes on meaning through place; and each part (i.e. each place) in its interconnection with other parts (places) engenders the space of the whole” (Merrifield, 1993: 52). Martin (2003) suggests examining the neighbourhood through Agnew’s (2005) three meanings of geographic place. Accordingly, the neighbourhood would be seen as (1) a location or objective geographical area in space, defined by broader economic, political and social processes, and connected to other locations through interaction and movement; (2) a sense of place, that is, the subjective feelings, identification, symbolic meanings, representations and values attached to a place; and (3) a locale or setting where everyday life activities take place – “[h]ere the location is no mere address but the where of social life and environmental transformations” (ibid.: 89). Examples of such neighbourhood locales could be playgrounds, the schoolyard or street corner. Agnew (2005) writes that any attempt at putting place and space together should bring at least two of these meanings of place together. Thus, we could relate neighbourhood as a ‘location’ (geographic area) to ‘sense of place’ through how it is experienced by the people that inhabit it. As Martin (2003) points out, this conceptualization of place captures many of the aspects of neighbourhood identified in the literature, but which are not always captured in neighbourhood effects research – for example, how people

182 Chapter 6 project feelings on and invest places with meaning. Indeed, she asserts that much of what gives neighbourhoods salience are the “individual and group values and attachments” associated with them, which “develop through daily life habits and interactions” (ibid.: 365). Understanding how people give such meaning to neighbourhoods, and how, when and for what purposes they then draw on this meaning (e.g. in identify formation, claiming their turf, gentrification disputes, neighbourhood stereotyping, ‘reading’ place), is thus an important part of neighbourhood research. Place is seen as a constitutive component of human agency, social action and identity (Bauder, 2001; Gotham and Brumley, 2001; Massey, 1994). As Gotham and Brumley (2001) assert, “[u]rban spaces shape and condition how individuals and groups think and conceive of themselves, cultivate and develop personal and collective identities, and contest as well as reinforce prevailing meanings of race, class, gender, sexual orientation, and other social inequalities”. While the rapidly growing literature on children and youths’ geographies examines many of these issues (e.g. Reay and Lucey, 2000a; Thomas, 2005; Valentine, 2003), this literature remains largely distinct from that which examines neighbourhood effects on young people. In describing their neighbourhoods, the youths were perceptive of how they thought others viewed their neighbourhoods and how they thought their neighbourhoods had changed over time. In both describing their neighbourhoods (“what does your neighbourhood look like?”, “how would you describe it?”, “what people live there?”) and how they had changed over the years, the ethnic composition stood out as a distinguishing feature. This was also the case for their schools. Mirak explained that his neighbourhood in Amsterdam Zuidoost “really went downhill”, but that when he “grew up there it wasn’t like that”. When giving his impression of how his neighbourhood had changed he referred to the ethnic makeup of his older brother’s class: “like when you look at my brother, he had like 50 percent white kids in his class and only one of them remains [in the neighbourhood], that’s pretty much a good example of what happened in the community”. Youths’ descriptions of their neighbourhoods (and in some cases schools) involved references to things they had heard through the media or to the fact that their neighbourhood was a target area for government programmes. Martin and Miller (2003: 148) comment that “[t]he meaningful construction of places by capitalists, planners, communities, social groups, religious institutions, and media shape place-specific notions of fear, safety, comfort, and belonging”. One of the youths explained that “the mayor of Amsterdam said it [his neighbourhood] is a crisis area right now, a problem area, and it wasn’t like five years ago, it wasn’t

One-sided geographies? 183 labelled as such, but now it is, so it has really gotten worse in a short amount of time”. Another youth explained that by the time she was finishing secondary school, her school had gotten “a worse reputation. It also came in the news and police reports. Now that I’m no longer at the school, the students who are still there tell me that a lot of bad things are happening there”. Several of the youth were critical of media representations of their neighbourhood (and, in one case, their school). Louis commented about his former neighbourhood, in Zuidoost: “[y]ou know, there’s a lot of crime, I mean too much, but sometimes I think people also exaggerate you know, because when you look in the news you see like a lot of black people, and it’s like ‘ok, all of them are like that?’, you know, it’s sad” (his emphasis). Several of the other youths also expressed remorse about what they perceived to be ethnic discrimination in the media, and sometimes specifically in their neighbourhoods and schools. Commenting on how she thought the Moroccan male youth in her neighbourhood are viewed, who are increasingly associated in the media and elsewhere with causing neighbourhood problems, Melissa said, “it’s really sad because not every Moroccan is like that and I think it’s sad because some people look bad to others, but they are good people”. When asked how she thought her neighbourhood was viewed by outsiders, Besma was somewhat reluctant to elaborate:

Interviewer: How do you think your neighbourhood is seen by outsiders? Besma: Yeah, I wouldn’t really know. A deprived neighbourhood [achterstandswijk] or something. Interviewer: Yeah? Besma: Yeah, it was really just a neighbourhood with people with middle- or low-incomes and big families and mainly ethnic minority children were there. So. Interviewer: But did you feel that it was (deprived)? Besma: No, not really. It was nice and friendly [gezellig] and as long as I had fun the rest didn’t matter to me.

Later on in the interview, it was apparent that Besma not only dealt with negative stigma attached to her neighbourhood, but also to her school. She was among the first few cohorts of students to attend the Islamic secondary school in Amsterdam, and explained that:

184 Chapter 6 it was a new school and being a Muslim school, it was badly portrayed in the media several times…From outside, people look in, like, ‘Oh you go to the ICA, that’s a really bad school, worst school in Amsterdam!’. But I barely noticed, and look, now I’m at HBO, second year, so, if it really is such a bad school…

She explained that attending that school taught her, among other things, to be more critical of the media: “[f]or me, it was a good school. And it taught me things that I’m glad about, in terms of faith, in terms of others things – like that you can’t only look at what the media says”. A number of studies have examined how representations of place have an impact on young people’s identity constructions (Bauder, 2001; Hollingworth and Archer, 2010; Wridt, 2004). Based on interviews with 21 youth in San Antonio, Texas, Bauder (2001) argues that cultural representations of neighbourhood and place-specific ideologies intervene in the formation of inner-city youth identities. Labels of ‘deviancy’ and ‘social pathology’ are inscribed on neighbourhoods and affect how youth formulate their identities. Drawing on the work of Lefebvre, he asserts that identity and ideology cannot be seen as aspatial – “ideological structures are represented in and through space and place” (ibid.: 281). Smith (1999: 139) also suggests that

[i]t may only be meaningful to consider identity, and therefore also difference, with reference to particular places at particular times. Place matters if we want to understand the way social identities are formed, reproduced and marked off from one another. Where identities are made is likely to have a bearing on which markers of difference – class, gender, and ‘race’ and so on – are salient, and which are veiled (quoted in Martin and Miller, 2003: 147, emphasis in original).

In their research on children who live in inner-city London council estates that have been “pathologised in both the national and local media”, Reay and Lucey (2000a: 415) comment that “if, as Thrift asserts, ‘place and identity are inexorably linked’, then the places in which these children live present them with a dilemma”. During their research, the research area had been described in the press as ‘drug ridden’, ‘full of problem families’ and ‘hot beds of crime’. Consequently, they explain, “the children we interviewed were often caught up in dominant imaginary constructions of the urban poor at the same time as they tried to convey their own different, locally constructed realities” (ibid.).

One-sided geographies? 185 Melissa explained how she thinks her neighbourhood Slotervaart is viewed by outsiders:

Melissa: They see it like the ghetto10. Interviewer: Really? Melissa: Really, and that comes, because in the news, there are a lot of things in the news, bad news, and that’s because there are a lot of immigrants [allochtonen] living there and they make trouble, a lot of trouble. Sometimes I say to people ‘Yeah, I live in Slotervaart’ and I’m very excited about it, and they say, ‘You live there? In that neighbourhood? Are you not scared to go alone on the street?’. So people think it’s very bad, that the neighbourhood is bad, but it’s ok.

I asked her whether she thinks anyone would judge her for living there, trying to understand if, in her view, the bad reputation would possibly have a negative impact on her. She was quick to answer:

Oh no, no, no. That’s because, I’m white, I think they [other people] see me as white. Because I’m an ethnic minority too, because one of my parents is born in Asia, so I’m foreign also, but they see me as a white girl, so they think, ‘Oh poor girl, do you live there, in that neighbourhood?’ and I think ‘Yeah, it’s ok there, there’s no problem at all!’.

I asked her about the ‘trouble makers’ and whether they actually do make trouble and if it affects her. She explained,

they really make trouble. Young boys, between 12 and 16. They are hanging out on the street, they destroy cars, or talk to girls that don’t want to talk to them, that kind of stuff, sometimes with weapons or they fight each other, with a bad ending, really, like somebody stabs each other, or with a pistol…Of course, you also have Dutch bad boys, not only Moroccan bad boys.

10 It should be noted, that several of the youth use the term ‘ghetto’ very freely. There are in fact no ghettos in Amsterdam, although several referred to their neighbourhood or other neighbourhoods as ‘the ghetto’ or ‘kinda ghetto’.

186 Chapter 6 She explained that despite this, she really likes the neighbourhood and thinks it is a good place to live. She knows her way around and she knows the youth who cause trouble and they don’t bother her: “[t]hey don’t bother me though. Because I’ve lived there now for 20 years, they know me, so they leave me alone. It’s a good neighbourhood, really”. Overall, the quantitative analyses of the larger project (Sykes and Kuyper, 2009; Sykes and Musterd, in press), and students’ descriptive accounts in the interviews reported here, suggest both the subtle – and even incidental – and more complicated ways in which their neighbourhoods have meaning for young people. Several youths, at age 21, still had the same best friends who grew up down the street from them. Some of them made their secondary school decisions together with their neighbourhood friends. Nearly all attended the closest primary school to their house, and remembered well the journey to school every day. They were perceptive of how the image of their neighbourhood was seen by others. Some expressed a positive identification and attachment to their neighbourhood – it was their favourite place in Amsterdam and where they really felt at home and safe in the city. Some expressed the desire to remain living in their neighbourhood, even after they moved out of their parental home, suggesting the way in which residential location is often reproduced in families (cf. Mulder, 2007). Others expressed a dis-identification with the neighbourhood. Louis was tired “of the mentality” of the people in his former neighbourhood, which had “changed a lot” over the years and was glad to have left it. Mirak was also tired of the problems in his neighbourhood and he and his mother were looking to move out. After he had a close call with “five guys in their 20s” who tried to hit him with a brick while he was on his bike, he said, “that really got to her [his mom], like ‘Ok, this is not a good area to live’”. He said the neighbourhood was “peaceful” when he was growing up, but that it had changed a lot and his mother and him often spoke about it:

there’s a lot of crazy things going on right now. There was, at the exit of the subway station they did a random check of people, and over the course of a week they found like 10 pistols, 3 sub-machine guns or something, pretty crazy. Two weeks ago there was a shooting at [the] shopping mall and there’s robberies almost every month there, so she [his mom] has the feeling that maybe it’s time to go.

However, many of the ways in which their neighbourhoods seemed relevant to the youth, and the diversity of experiences within even this small sample of youth, are not captured in most neighbourhood effect analyses. Several drew upon their

One-sided geographies? 187 experience of living in multiple neighbourhoods. Louis lived in Zuidoost until he was 15 years old, then moved with his parents to Amsterdam West, and had also worked part-time at a sneaker shop in the city centre (Centrum) of Amsterdam. He was happy to have left Zuidoost and commented, “to be honest, you got a little bit tired about how things were evolving in Amsterdam Zuidoost, it has a bad name, but you know when we moved over there it was like quiet, not a lot of drugs or violence you know…everything was totally different”. He made several references to the different “mentalities” he perceived in different parts of the city (especially contrasting Amsterdam Zuidoost and the city centre). Referring to Zuidoost, he explained:

My parents got a little bit tired of the mentality people have, you know, going to Kwakoe11 all the time, I mean, there’s more to life than going to Kwakoe. You know, but I have to say that because I grew up in different parts of the city, I’m more, I see things from a different perspective, you know. I had the chance to get to know other people, because people in the sneaker scene who live in the centre of Amsterdam, they know nothing about Zuidoost, but I do, I know the mentality of these people (points to Zuidoost on the map), and these people (points to West), and these people (points to Centrum). You know, so combined, I think I know more about Amsterdam than people who grew up only in Amsterdam Zuid, you know. Because we have friends from Amsterdam Zuid, like rich people, you gotta have a good income to live there, you know, I also talk to those people, so I think in the end, it was good for my development [to grow up in several neighbourhoods], because I think if I had lived just here (Zuidoost) I would be a totally different person.

Several of the other youth also interpreted different ‘mentalities’ or read different ‘attitudes’ off the places they lived and other parts of Amsterdam. They often made reference to the ethnic diversity of their neighbourhoods (and sometimes schools), and how they thought this affected them. As mentioned above, Esther grew up in an ethnically diverse part of Amsterdam Noord, but later attended a Montessori school with a predominantly (80 percent) native Dutch student body. She reflected on her experience:

11 Kwakoe is a well-known summer festival, located in the Bijlmer neighbourhood of Amsterdam, which “has become the major focal point for celebrating “Black culture” in the Netherlands” (Aalbers, 2010: 10).

188 Chapter 6 So [growing up] I’d go to Moroccan parties, like marriages and stuff like that. So that’s what I knew. Then I had these friends [in secondary school] who were Dutch, and they took me to their parties and I didn’t understand anything of it, so plain and dull, and ‘why is no one dancing?’, and they would say ‘well that’s the Dutch way of partying’, so yeah that’s different. I have a different view on immigrants and Islam for example, because I grew up with it, so I can relate to it, I don’t believe in it, but I know a lot about it, and that made me different, and I can see it still. So now I study, and it’s a real white study, we have like four black girls and they’re all from Suriname, and nothing else, the rest is Dutch, and they really don’t understand the Islamic people or the Surinamese people…That’s really different, the understanding and tolerance.

6.8 Conclusion In this paper I have drawn attention to some of the challenges and opportunities involved in researching neighbourhood effects on young people. I have argued that in order to understand how neighbourhoods are relevant for young people, it is necessary to appreciate how youth interact with neighbourhood places (e.g. how they choose, discover, understand, and interpret their neighbourhoods) and how neighbourhoods relate to other places (e.g. schools) within and beyond the neighbourhood. Neighbourhoods are experienced in different and complex ways by young people. These experiences are shaped by a number of factors, including how young people perceive or interpret their neighbourhood, the others places they spend time in, and perhaps also their gender, social class and ethnic background. One of the factors that I have highlighted in this paper is young people’s schools. I have suggested a shift of attention from focusing primarily on (direct, independent) effects of neighbourhoods, and instead thinking about the influence of neighbourhoods as the product of many interconnected factors, which cannot easily be ignored in the study of neighbourhoods and people. This includes issues widely recognized in the neighbourhood effects literature, such as the non- random sorting of populations into neighbourhoods (i.e. selection effects), but also notions more common in the geographical literature on place and space. As others have suggested, the study of neighbourhood effects could be more ‘place- sensitive’ by acknowledging the uniqueness and specificity of neighbourhoods

One-sided geographies? 189 and the multiple meanings of ‘place’. The ‘neighbourhood effects’ that might exist in one place could well be the function of local specificities, rather than the result of a generalizable relationship. Moreover, youth deserve a more prominent role in the discussion of and research on selection effects. It was clear from the interviews that youth not only played an important part in choosing their secondary schools, but school choice factors that have been researched with respect to adults – such as the ethnic mix of schools – were also relevant for them. How we view neighbourhoods and their effects on people has both intellectual and societal implications. A number of scholars have suggested that the emphasis on neighbourhoods as a source of social problems and social disadvantage has helped to support policies aimed at finding ‘solutions’ to these problems in the neighbourhood, for example by promoting social mixing, community cohesion and neighbourhood social capital, even though these initiatives fail to challenge the root causes of the problems or deliver the expected benefits to low-income households (Amin, 2007; Bauder, 2002; Fallov, 2010; Lupton and Tunstall, 2008). The idea of a one-way neighbourhood effect on youth bears little resemblance to their actual experiences in multiple neighbourhoods and the everyday realities of most youth growing up in a city. Neighbourhood effect research might gain from paying more attention to what a neighbourhood actually means in the lives of young people. Moreover, bringing together research on young people’s geographies, school experiences and neighbourhoods could be useful in broadening the framework of neighbourhood effects. It was evident from many of the interviews that youth are highly aware of the discursive representations of their neighbourhoods and schools, especially those related to ethnically diverse and majority-white schools (termed ‘black’ and ‘white’ schools in the Dutch discourse) (cf. Paulle, 2002). In understanding the impact of place, it makes sense to consider how these external influences also affect youths’ experiences in and interpretations of their neighbourhoods and schools. Neighbourhoods and schools do not operate independently of their external context. As Lupton (2003) describes, there are tensions between the conceptual and methodological approaches of quantitative and qualitative neighbourhood effects research. This paper highlights some of these tensions, not in an attempt to privilege one methodology over the other or to engage in a discussion of methodological orientations, but in an attempt to demonstrate some of the challenges that need to be addressed in order to further our understanding of the role that neighbourhoods – and more broadly, spatial segregation and socio- spatial inequality – play in the lives of young people.

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One-sided geographies? 193 7 Conclusion and discussion

7.1 Introduction This book has engaged with literature and debates on neighbourhood effects, segregation, school effects and neighbourhood social mixing policy. The aim of this book was to assess the extent and nature of neighbourhood effects on youth outcomes, to test whether neighbourhood effects on youth are transmitted through the school context, and to work towards combining the study of neighbourhood and school effects on youth. A broader aim of this study was to assess the usefulness of the neighbourhood effects framework for understanding the relationships between youth, their social outcomes and neighbourhood inequality. Chapters 2, 3 and 4, based on quantitative analyses, empirically examined the evidence for neighbourhood effects and school effects on youth and the relation between these two effects, while Chapters 5 and 6 dealt with conceptual issues in the study of neighbourhood impacts and reflected more critically on the notion of neighbourhood effects. In this concluding chapter, I bring together the main findings of each chapter and reflect on their implications for other studies. I offer suggestions for future research, outline what I see as limitations of the neighbourhood effects framework, and discuss how this framework might be complemented and enriched. To recap, the following research questions were addressed in this book:

1. Can neighbourhood effects on youths’ educational outcomes be identified and if so, what is the nature and extent of these effects? (Chapter 2) 2. Does the socioeconomic or ethnic composition of the school have an effect on youths’ secondary school outcomes? (Chapter 3) 3. Are neighbourhood effects on youth transferred through the school context? (Chapter 4)

7.2 Summary of research findings 7.2.1 Neighbourhood effects on education? At the most basic level, the current research demonstrates that educational outcomes are unevenly distributed across neighbourhoods in the Netherlands. We can speak of a ‘geography of educational inequality’ in the Netherlands. And this geography is not trivial: on average, 28 percent of the variance in students’ achievement in secondary school (as measured by standardized tests in either the

Conclusion and discussion 197 first or third year) is associated with the neighbourhood level1. An example more familiar to those in the Netherlands comes from the 2010 Amsterdam Cito-test results and recommendations for secondary school, reported per city district for the 95 percent of primary school students who took part in the test (Waijenberg, 2010). Even at the city district level, a geographical patterning is recognizable; around 80 percent of the children living in Centrum and Oud-Zuid received a HAVO and/or VWO recommendation, while for children in Zuidoost this was 33 percent, and 38 and 40 percent for those in Geuzenveld-Slotermeer and Noord respectively2 (ibid.). This geography has a lot to do with the various factors that sort and sift people across space and thus generate and maintain socio-spatial structures. For example, the similarity in housing types and prices generally found on a street or in a larger area ensures some degree of similarity in the social class or income level of the residents. Although overall levels of socioeconomic segregation in the Netherlands, as measured by conventional segregation indices, are comparatively moderate (Musterd, 2003), there are higher- and lower-income areas, and neighbourhoods where more or less affluent households cluster. This socioeconomic patterning across space is relevant for education because in the Netherlands, and elsewhere, school choices and educational outcomes are associated with socioeconomic status. Thus, it is well-known that there is a geography of educational outcomes in the Netherlands. But, are there ‘neighbourhood effects’ on educational outcomes? This was the research question that instigated this dissertation: Can neighbourhood effects on youth educational outcomes be identified, and if so, what is the nature and extent of these effects? To first address this question, a multilevel model was specified in Chapter 2, in which the first year secondary school achievement scores of around 18,000 youth were analysed. Levels of achievement were found to be considerably clustered at the neighbourhood level, with more than one quarter of the variance attributable to the neighbourhood level (i.e. differences between the neighbourhoods). The vast majority of this clustering was explained by differences across neighbourhoods in terms of the characteristics of the people who live there, indicating what are often referred to as ‘composition effects’ (i.e. correlation in the outcome variable due to the

1 As described in previous chapters, ‘neighbourhood’ in this study is operationalized as the buurt. ‘Buurten’ are administrative spatial subunits representing the lowest neighbourhood level in the Netherlands. These areas vary in terms of population size and surface area and tend to be defined on the basis of natural borders, such as roads, rail- and waterways, parks, and by building styles and periods. 2 The Cito-test is a standardized test taken at the end of primary school, which largely determines one’s place in secondary school. The HAVO and/or VWO recommendation includes the highest two (out of five) tracks of secondary school, which prepare students for, and allow entry into, university education.

198 Chapter 7 socioeconomic patterning of households across space, as described above). However, support for neighbourhood effects over and above these composition effects was also found, suggesting that there are neighbourhood effects on youths’ educational achievement. The neighbourhood characteristics in the analyses improved the fit of the model and accounted for around five percent of unique neighbourhood variance in achievement, indicating that neighbourhood conditions help to explain some of the differences in youths’ educational achievement. The findings indicate that youth living in economically better-off areas attain higher levels of educational achievement than those in more economically disadvantaged areas, over and above background characteristics such as gender, age, parental education, family structure and ethnicity. This relationship, however, is not uniform across all groups of youth. Effect heterogeneity across youth socioeconomic background and native Dutch/minority ethnic background was found. The achievement outcomes of youth from families with higher levels of socioeconomic resources appear to bear a weaker relationship to their neighbourhood conditions than those of youth with lower levels of socioeconomic resources; the achievement outcomes of youth with a minority ethnic background appear be related to the level of neighbourhood affluence, but not socioeconomic disadvantage3. Thus, I conclude from these findings that the relationships between neighbourhood conditions and youth outcomes are likely to be obscured in studies that measure average neighbourhood effects across all individuals. Indeed, there is no a priori reason to believe that all individuals are influenced by neighbourhood conditions in the same way; rather, there is much evidence pointing to the diverse ways in which places are experienced, and how this can be shaped by factors such as social class, gender and age (Reay and Lucey, 2000). Taken at face value, the results from Chapter 2 provide support for the existence of modest neighbourhood effects on youth school outcomes, which operate above and beyond youths’ background characteristics. The results of Chapter 4 also support this finding. The empirical magnitude of these effects is in line with several other Western European studies and is considered to be small, but not inconsequential. Determining the practical importance of (even statistically small) neighbourhood effects is a topic of ongoing discussion, which I deal with below.

3 In this paper, the constructs ‘neighbourhood affluence’ and ‘neighbourhood socioeconomic disad- vantage’ are the result of a principal components analysis of neighbourhood characteristics and are essentially made up of the following variables: average income per resident and per income earner; the share of high-income residents (i.e. affluence); and the share of unemployment benefit recipients and of low-income residents (i.e. socioeconomic disadvantage).

Conclusion and discussion 199 These results, however, have to be viewed in the context of several important caveats, which have been described extensively in this book, and which I briefly outline here. Importantly, although the word ‘effects’ is used loosely in social science research to refer to statistical effects, the ‘neighbourhood effects’ I find, as those found in nearly all non-experimental quantitative analyses, are in fact empirical associations, not estimates of causal effects. The variables used in these models (e.g. neighbourhood socioeconomic disadvantage) are constructs that serve as proxies for the social processes thought to drive effects. The mean neighbourhood income level does not have a direct effect on youth education, but processes associated with neighbourhood socioeconomic status might. Finding out which social processes drive the neighbourhood effects found in quantitative models requires ongoing work and collaboration between qualitative and quantitative researchers. Because there is a necessary trade-off between data representativeness and the ability to comment on broad relationships on the one hand, and contextual understandings and the ability to uncover complex social processes on the other, the methodology I adopt in Chapter 2 does not enable me to explore the intervening social processes that might explain the associations I find. Thus, I find support for the existence of neighbourhood effects on youth educational outcomes; the next question is, why would this be so? The literature points to a number of processes thought to drive neighbourhood effects, including those tied to institutional resources and structural factors (e.g. the quality and nature of schools, childcare facilities and public service provision; institutional gatekeeping practices; neighbourhood stereotyping), social-interactional mechanisms (e.g. peer relations, socialization, social networking, the setting of social norms), and selection effects (e.g. the non-random processes through which people come to reside in certain neighbourhoods, which may affect not only the place of residence, but also the outcome variables). In my view, these are not competing but rather interrelated explanations for neighbourhood effects, and the results I find are likely the outcome of multiple factors related to each of them. The intervening pathway of neighbourhood effects that I focused on in this book, and discuss next, is the school.

7.2.2 Neighbourhood and school effects: Considering two contexts If the neighbourhood context is important for young peoples’ development and outcomes, schools are arguably one of the most important reasons for this. In the theoretical literature on neighbourhood effect mechanisms, schools are posited to be one of the local institutions that contribute to place-based effects (Sampson

200 Chapter 7 et al., 2002; Galster and Santiago, 2006). There are two main reasons for this. First, schools, as institutional resources operating in a quasi-market system, vary in terms of their quality and effectiveness, attractiveness to parents and teachers, features and programme offerings, atmosphere, and so on, and thus, school characteristics differ across place. Secondly, and relatedly, schools bring local children, youth and their families together, and processes such as socialization and learning, peer relations and social networking, take place in and around the school. As the neighbourhood plays a role in sorting students into schools and in shaping families’ school choices, schools are where some of the ‘neighbourhood effects’ could occur. Chapters 3 and 4 examined the extent and nature of school effects on youths’ school outcomes, and whether the school serves as a pathway of the neighbourhood effect, addressing the second and third research questions respectively. The results of these chapters provide support for the notion that some of the influence of the neighbourhood is transferred through the school context. Chapter 4 examined whether the observed relationships between neighbourhood conditions and youths’ school outcomes are explained by the schools they attend: Are neighbourhood effects on youth transferred through the school context? By specifying a cross-classified model, the analyses in Chapter 4 took youths’ membership in neighbourhoods and schools into account and concurrently estimated the ‘effects’ of both of these contexts. The results reveal that once school effects are taken into account, there are no statistically significant neighbourhood effects remaining, suggesting that the school does indeed transfer a large part of the observed neighbourhood effects. Although the original aim of these analyses was to incorporate the school into neighbourhood research by testing whether schools are a pathway of the neighbourhood effect, the story is more complex than schools simply mediating neighbourhood effects. While it is reasonable to believe that some of the influence of the neighbourhood is transferred through the school context, implying that the school is a pathway or mechanism of the neighbourhood effect, not all young people attend a school in their home neighbourhood. Although for many children their primary school is located in their home neighbourhood, this is less often the case at the secondary school level. Thus, the findings of Chapter 4 are bound to be partly the result of confounding between the school and neighbourhood characteristics experienced by youth. This calls for further analysis, which considers separately those who are educated locally and those who are not. A broader issue is the complexity of separating out the influence of contexts, which we know are in fact related (e.g. the neighbourhood, school, family). Although we can analytically and methodologically separate ‘neighbourhood

Conclusion and discussion 201 effects’ from ‘school effects’ (and from ‘family effects’), in reality these factors are interconnected, and thus, the actual causal pathways of these effects are bound to be intertwined. For example, a family’s residential decisions may be related to their choice of schools for their children, both of which are known to be related to family social class background. Commenting on the intertwined effects of home, neighbourhood and schools, Pacione (1997: 176), remarks that “[w]hile seeking to disentangle this complex has pedagogic value, disaggregation is an artificial exercise which does not reflect the totality of the local educational environment”. This issue is discussed further below. Chapter 3 zeroed in on school effects. The chapter examined the relationships between school characteristics and student outcomes, with a special view to the inequalities in educational achievement between ethnic and socioeconomic groups and their potential relationship to school segregation. A number of studies find that levels of school segregation in the Netherlands are comparatively high, for both primary and secondary education. School segregation reflects patterns of residential segregation, but is known to be reinforced by institutional features of the school system, including open school choice and family school choice decisions, and academic tracking at the secondary school level. One of the main reasons that school segregation is a cause for concern is the worry that it generates or reinforces educational inequalities. The differences in school performance between different social and ethnic groups raise questions about school conditions which might be unfavourable for students’ educational development, and school segregation is seen as potentially being one of these conditions. Chapter 3 tested the effects of school ethnic and socioeconomic composition on youths’ school outcomes in Year 3 and Year 5, taking youths’ prior achievement in Year 1 into account. This ‘control’ for prior achievement means that the analyses tested specifically for the effects of school composition in secondary school. The results indicate a negative relationship between school ethnic composition and students’ third year achievement, but not Year 5 position; however, this relationship was entirely explained by differences in school socioeconomic status. Thus, as other studies have found, school socioeconomic status is associated with students’ educational outcomes in the Netherlands, over and above individuals’ prior achievement, socioeconomic status and other background characteristics. Because school ethnic segregation is tied to socioeconomic segregation, segregation along both ethnic and socioeconomic lines appears to be relevant for students’ school outcomes. The results of Chapters 3 and 4 point to school effects that are tied to school composition and underscore the need for more research which considers school

202 Chapter 7 and neighbourhood effects together. Just as in Chapter 2, the school effect analyses do not uncover the actual processes driving the observed associations between school characteristics and youths’ educational outcomes. Likewise, it is not simply high-socioeconomic status (SES) peers that create a positive school effect; rather, school research suggests that student body composition, teaching and classroom processes, school management and organization, and external factors, interact with each other in complex ways (Gewirtz, 1998; Hattie, 2002; Thrupp et al., 2002; Lupton, 2005). This has importance for how we think about school composition effects and school mixing policies. Importantly, even after taking a key set of individual background and school characteristics into account, including youths’ prior achievement levels, the analyses in Chapter 3 reveal that several minority groups perform worse relative to the native Dutch majority, and that low-SES groups perform worse than their higher-SES counterparts. The social and ethnic composition of the schools these youth attend do not account for this educational disadvantage. These performance differences are, however, more pronounced for the achievement test outcome in Year 3 than for the school position outcome in Year 5; in terms of school position in Year 5, the differences between ethnic groups are smaller and some minority groups perform better than the native Dutch group. Taken together, the results of Chapters 2, 3 and 4 all reveal persistent differences in educational outcomes across socioeconomic and ethnic background, even after taking individual socioeconomic status, school characteristics, neighbourhood characteristics, and in some analyses, prior achievement, into account. Such systematic differences in educational outcomes are worrying, especially given that government measures explicitly aim to redress educational inequalities. This does not necessarily imply that government interventions have been ineffective; moreover, minority ethnic groups have made steady headway in terms of levels of educational attainment and there is no reason to believe that differences across ethnic groups in educational achievement are permanent. While most would agree that education is a critical factor in future labour market outcomes and life chances, and that in advanced capitalist societies those with higher levels of education receive more (economic) rewards, it is also not the case that everyone aspires to high levels of education. However, the relationships between socioeconomic and ethnic background on the one hand, and educational outcomes on the other (e.g. the socioeconomic gradient – the link between parental educational background and individual educational background), vary widely across different national contexts (Schnepf, 2007; Willms, 2010), and thus, finding out what drives this variation, and how to create a more level playing field, is an ongoing task for those concerned with social justice

Conclusion and discussion 203 in education. From this perspective, the results of this book show that many of the standard predictors used in models of educational achievement (e.g. gender, age, ethnicity, socioeconomic status, prior achievement, school SES, school type), in addition to youths’ neighbourhood characteristics, do not fully account for observed differences in educational outcomes, particularly across socioeconomic lines. Other factors are at play.

7.2.3. Neighbourhoods, their effects, and social mix: The policy and research context Chapter 5 shifted gears and examined the policy context surrounding neighbourhood restructuring and neighbourhood social mixing initiatives. There is a good deal of work that connects the neighbourhood effects framework to government social mixing and poverty deconcentration initiatives, both in North America and Western Europe (Curley, 2005; Lipman, 2008; Lupton and Tunstall, 2008; Fallov, 2010). It has been argued that the notion of neighbourhood effects lends support to the current policy focus on promoting ‘socially mixed’ neighbourhoods and ‘cohesive communities’ as part of the answer to the problems of poverty and social inequality. The idea of socially mixed neighbourhoods has strong appeal; as Smith (2002: 98) points out, “‘[s]ocial balance’ sounds like a good thing – who could be against social balance?” However, looking more closely at how social mixing initiatives are implemented, the assumptions underlying these strategies, and the research findings to date, cautions against accepting these policies uncritically. Certainly, not all attempts to promote socially mixed neighbourhoods can be criticized, but much literature suggests that the objectives of social mixing initiatives are often blurred between promoting endogenous neighbourhood revitalization and promoting broader gentrification processes. And importantly, research finds weak evidence supporting the expected positive effects for incumbent households. One of the key interests of Chapter 5 was the notion that the neighbourhood effects framework might work to inspire, or legitimize, neighbourhood social mixing policies. It has been suggested that the emphasis placed on neighbourhood effects has inadvertently lent theoretical and empirical weight to the idea that neighbourhoods are (at least in part) responsible for their own social problems, and hence, that solutions to these problems lie in the neighbourhood and its population mix. In calling attention to the neighbourhood and its social composition, attention may be shifted away from the institutional and economic constraints that individuals face and from more fundamental determinants of poverty and inequality. In the US discussion, scholars have argued that the extensive use of the concept of ‘concentrated poverty’ to describe the conditions

204 Chapter 7 in poor neighbourhoods has led to an important theoretical slippage, whereby concentrated poverty has come to be seen as an underlying cause of poverty, and thus deconcentrating low-income households is seen as an effective means of tackling poverty. While it goes without saying that researchers should always be specific and careful in their analyses and specifications, one of the main messages that emerges from Chapter 5 is that even more can be done to improve this in the field of neighbourhood effects research. A number of commentators have argued that there has been an over-reliance in neighbourhood effects research on often crude proxies, and a tendency to centre attention on behaviour which diverges most from so-called middle-class standards. There is often an implicit assumption that growing up or living in a poor neighbourhood must constitute a negative force in one’s life, even though there is a great diversity of experiences and social outcomes in even the poorest (and richest) neighbourhoods. This within-neighbourhood heterogeneity is often overlooked in neighbourhood studies. Moreover, the forces that produce and reproduce neighbourhood social structure are given little attention in most neighbourhood effects frameworks, and thus, there is a risk of overemphasizing the role of the neighbourhood and its social composition, at the expense of obscuring wider structural forces. As Wacquant (2008: 9) writes, “[t]o forget that urban space is a historical and political construction in the strong sense of the term is to risk (mis)taking for ‘neighbourhood effects’ what is nothing more than the spatial retranslation of economic and social differences” (emphasis in original). While I do not believe that neighbourhood effects are merely the reflection of broader differences in society, I think more attention has to be given to the processes – including those beyond the neighbourhood – that generate and maintain neighbourhood and individual social inequalities. Understanding the effects of neighbourhoods requires an understanding of how these places are produced. This would give a more balanced picture of neighbourhood effects, and would, in my view, oppose the spatial deconcentration of poverty as an effective means of promoting individual social mobility. Most neighbourhood effects researchers are well aware that they are working with imperfect proxies when they use census tracts or administrative units to define neighbourhood and aggregate population characteristics to represent neighbourhood conditions. However, for large-scale studies, time and cost constraints necessitate some degree of reductionism. Moreover, there exists no perfect proxy for ‘neighbourhood’; as outlined in Chapters 1 and 6, people’s sense of neighbourhood may vary depending on the activity in question, their age, and multiple other factors, just as the neighbourhood of interest to researchers may

Conclusion and discussion 205 vary depending on their topic of investigation. In my view, these are valid starting points for exploring geographical differences and neighbourhood effects, but there is also a pressing need for more collaboration between qualitative and quantitative researchers and more nuanced data.

7.2.4. Above and beyond the neighbourhood: Extending the framework Chapter 6 followed from the previous chapter and explored some of the challenges in researching and understanding the meaning and role of the neighbourhood in young peoples’ everyday lives and longer-term social outcomes. While some of these challenges stem from methodological difficulties inherent in trying to measure the influence of complex social contexts, they also include conceptual issues concerning the definition and interpretation of ‘neighbourhood’ and how we conceptualize the relationship between neighbourhoods and people. I focused on how we view neighbourhoods and especially how we view their relationships with, and effects on, young people. I argued that neighbourhood effects research could better link up with (the mainly geographical) literature on place and space. Linking up with this literature would compel us to ask not only how neighbourhoods influence individuals, but also how individuals influence and interact with neighbourhoods – that is, how individuals come to be in particular neighbourhoods, and how they interpret, shape, draw on and give meaning to these places. The main argument of Chapter 6 is that the neighbourhood effects framework could be enriched by thinking more explicitly in terms of overlapping and reciprocal relationships running between (multiple) neighbourhood places, places of education (e.g. schools), and young people, with these relationships embedded in a wider system of institutions and socio-spatial practices. I showed, through young people’s descriptive accounts, that neighbourhoods do have meaning for their everyday lives, routine activities and probably also their longer-term outcomes, but that youth are also active in choosing and interacting with the places they encounter, including their secondary schools and places within and beyond their neighbourhood. The relationship between neighbourhood and individual should be thought of as mutual interaction, rather than a one-way effect of neighbourhood on individual. Youths’ reports of their residential histories and interpretations of neighbourhood boundaries underscore the multiple neighbourhoods that young people inhabit and the different ways in which they define and view these places. Rather than thinking of the neighbourhood as a bounded area or a context for social activity, it is helpful to view the neighbourhood through the geographical concept of ‘place’. From this perspective, the neighbourhood could be seen as a unique place with many

206 Chapter 7 overlapping places nestled within it, which have porous and dynamic boundaries and links to the wider world. Without taking a more holistic and relational view of the neighbourhood, or by reducing the neighbourhood to a few variables, we are bound to miss many of the characteristics that make it a meaningful place. The interview findings also show that the perspectives of young people merit a larger role in research on school and neighbourhood selection.

7.3 Overall conclusion Nearly no neighbourhood effects studies begin with the assumption that they will uncover ‘large’ neighbourhood effects on individual outcomes. We know that individual outcomes like educational attainment are the result of a combination of many interrelated factors, the most important of which concern individual and family characteristics, such as individual aptitude, motivation and interests, social class background, and parental level of education. However, individuals and their families are situated in, and react to, wider neighbourhood and social structures. Thus, individual interests, friendships, parenting behaviour and so on, may also be shaped by the neighbourhood setting. This study finds support for the existence of neighbourhood effects on youth educational outcomes. More precisely, youths’ educational outcomes were found to be significantly associated with characteristics of their neighbourhoods, over and above important background characteristics. However, neighbourhood characteristics do not play a direct role in youths’ school outcomes. What explains youths’ educational outcomes lies foremost at the individual level (prior achievements, aptitude, family socioeconomic status, family structure, gender, age, ethnicity) and the school level. Insofar as neighbourhoods shape school choices and school populations, which other research shows they do, neighbourhoods can be considered to have an indirect effect through those pathways. Neighbourhood conditions may also affect family functioning, parenting behaviour, and individual interests, which, in turn, may affect individual school outcomes. Thus, neighbourhood effects on young people’s educational outcomes can best be thought of as indirect and incidental. The extent to which a unique or independent neighbourhood effect can be accurately identified is questionable. Where young people live is related to the friends and peer groups they have while growing up, the schools they attend, and their families’ social class background, and thus, many facets of a young person’s social world are intertwined. It is widely recognized that by ‘controlling’

Conclusion and discussion 207 for variables which may themselves be affected by the neighbourhood context, it is likely that neighbourhood effect models often underestimate the true impact of the neighbourhood and confound possible mediating pathways. This calls for the need to take a more holistic approach to the study of neighbourhood effects, which considers the interactions between youth and the multiple places that they inhabit, both concurrently and over time. The analyses in Chapters 2, 3 and 4 support the notion that the neighbourhood is relevant for young people’s social outcomes, though determining the relative impact of the neighbourhood, versus the family or school context, for example, is probably impossible given the complex interconnectedness of these contexts. Thus, there are many reasons to look further into the role of the neighbourhood, and the interaction between neighbourhoods and youth, but ideally this should be conducted with an awareness of the interconnectedness among youth, their current and past neighbourhoods, schools, and homes.

7.4 Suggestions for future research This dissertation has resulted in a number of ideas and suggestions for future research, some of them already mentioned above. Above all, I suggest two ways in which thinking about and researching neighbourhood effects could be complemented and extended. I think it is necessary to complement neighbourhood effect studies with studies that adopt a more holistic and relational perspective. First, it is necessary to be more conscious of how neighbourhood space and neighbourhood social structure are produced and maintained. There is a vast geographical literature on the (re)production of uneven geographies; in my view, this literature helps to put the notion of neighbourhood effects into perspective. While inequalities across neighbourhoods have implications for individuals, the production of these spatial inequalities is not an arbitrary matter. The underlying causes of neighbourhood effects do not always lie in the neighbourhood. Thus, one could ask, for example, which social and structural relations underpin neighbourhood segregation? What do socio-spatial inequalities and neighbourhood effects reveal about the political, economic, social and cultural processes in which they are embedded? The production of neighbourhood geographies is also of direct importance to the issue of selection effects (or selection bias) in neighbourhood effects research. It is widely recognized that people do not come to live in neighbourhoods through random processes (and likewise, that children and youth do not come to attend certain schools through

208 Chapter 7 random processes). To understand the impact of place, it is important to view neighbourhood selection as a fundamental social process in itself and something of substantive interest to neighbourhood effects and to how neighbourhood structure is continuously made and remade. In the geography of education literature, a useful distinction has been made between inward- and outward-looking approaches (Hanson Thiem, 2009; Holloway et al., 2010). The inward-looking geography of education regards education to be the ‘ultimate ends of investigation’, with spatial variations in the provision, consumption and outcomes of schooling as topics of enquiry. The outward-looking approach is more instrumental, and uses these same patterns to comment on broader political, economic and social processes in society. In a similar way, much of the neighbourhood effects research could be classified as inward- looking. This research is often concerned with documenting and exploring spatial variations in certain characteristics and attributes (e.g. unemployment, income, collective efficacy), in an attempt to explain differential individual outcomes. This kind of analysis could be complemented by also thinking about what these neighbourhood patterns (or indeed, ‘neighbourhood effects’), say about wider, external social and structural processes. As Mitchell (2001: 1359) comments, “[y] ou cannot have a deprived place without deprived people, and it is social and spatial processes which bring deprived people together, hold them together, and continue their deprivation”. Secondly, I advocate a better awareness of the mutuality or reciprocal relations between people and the multiple places they inhabit and spend time in, including the neighbourhood. Although the neighbourhood is seen to affect individuals, how individuals shape the neighbourhood tends to be given little attention in neighbourhood effects research. There is a greater dialogue between people and place than is suggested by the notion of neighbourhood effects. The mutual relationships between people and place are a fundamental fact of human life and of key interest in some fields of study – people, place and space are always reciprocally interrelated (Massey, 1994). This issue is widely acknowledged in the neighbourhood effects literature (Leventhal and Brooks-Gunn, 2000; Buck, 2001; Sampson et al., 2002), yet still tends to be underappreciated. As Leventhal and Brooks-Gunn (2000: 331) explain, “in studying context, an important issue is the simultaneity problem, as addressed by transactional models of human development. Interactions between children and families are bidirectional in nature (Sameroff & Chandler, 1975). Those between families and neighborhoods may be as well”. Likewise, as Lupton (2003: 13) asserts, “there needs to be some mechanism for reflecting the interactions between people and place, in order not to identify neighbourhood effects that really arise from individuals, or vice versa”.

Conclusion and discussion 209 While this mutuality does indeed pose a significant challenge to measuring the ‘effects of neighbourhoods’, it suggests that we might look at the question of neighbourhood effects from a different perspective: not only how neighbourhoods affect people, but also how people affect neighbourhoods, including how they choose, are selected into, excluded from, shape, give meaning to, and interact with neighbourhoods. Taken together, these two interrelated points about neighbourhood selection/production and simultaneity/mutuality encourage neighbourhood effects researchers to broaden the lens through which neighbourhoods and their relationships with people are viewed, and to examine both sides of the person–place relationship. Diez Roux (2004: 1958) writes, “[j]ust as over simplification limits our ability to understand, the inability to simplify can be paralyzing”, and I agree. While it is necessary in research to reduce the complexity of the social world, still, we need to be cognizant of how our abstractions resonate with real world relationships. In this book, I made a several steps towards integrating neighbourhood and school research, but many more opportunities remain. At a very general level, asking how the school fits into the schema of neighbourhood effects (and vice versa, how does the neighbourhood fit into the schema of school effects?) are important questions. In neighbourhood research, the school is sometimes implicitly thought of as (part of) ‘the neighbourhood’, while in other studies it is contrasted with the neighbourhood (e.g. studies that find that neighbourhood segregation is not important for social ties, but suggest that school segregation may be). Neighbourhoods and schools are undoubtedly relevant to each other – for many youth, their schools are geographically embedded in or proximate to their home neighbourhoods, while for others, attending a certain school is a reason to leave their local neighbourhood. Some families’ residential and school choices are intertwined or made in tandem (Croft, 2004). In the realm of urban policy and research, there are many similar neighbourhood and school issues (e.g. neighbourhood and school segregation, neighbourhood and school mix policies). I think that the growing field of the ‘geography of education’ (e.g. Hanson Thiem, 2009) provides many opportunities to further develop knowledge about issues that concern neighbourhoods, schools and youth education, such as school choice processes (e.g. the spatial imprint of school choices), neighbourhood change and gentrification, residential and school segregation, and the pursuit of socially and ethnically mixed neighbourhoods and schools. In conclusion, further integrating qualitative and quantitative knowledge and research methods, and adopting a more place-sensitive approach to the study of neighbourhoods and people, will be important steps in moving forward in the field of neighbourhood research.

210 Chapter 7 References

Buck, N. (2001) ‘Identifying Neighbourhood Agenda’, Journal of Education Policy, 23(2): 119- Effects on Social Exclusion’, Urban Studies, 34. 38(12): 2251. Lupton, R. (2005) ‘Social Justice and School Croft, J. (2004) ‘Positive Choice, No Choice or Improvement: Improving the Quality of School- Total Rejection: The Perennial Problem of School ing in the Poorest Neighbourhoods’, British Edu- Catchments, Housing and Neighbourhoods’, cational Research Journal, 31(5): 589-604. Housing Studies, 19(6): 927-45. Lupton, R. and Tunstall, R. (2008) ‘Neighbour- Curley, A. (2005) ‘Theories of Urban Poverty and hood Regeneration through Mixed Communi- Implications for Public Housing Policy’, Journal of ties: A” Social Justice Dilemma”?’, Journal of Sociology and Social Welfare, 32: 97-119. Education Policy, 23(2): 13. Fallov, M. (2010) ‘Community Capacity Build- Massey, D.B. (1994) ‘Space, Place, and Gender’. ing as the Route to Inclusion in Neighbourhood Minneapolis, MN: University of Minnesota Press. Regeneration?’, International Journal of Urban Musterd, S. (2003) ‘Segregation and Integration: and Regional Research, in press. A Contested Relationship’, Journal of Ethnic and Galster, G.C. and Santiago, A.M. (2006) ‘What’s Migration Studies, 29(4): 623-42. the ‘Hood Got to Do with It? Parental Percep- Pacione, M. (1997) ‘The Geography of Educa- tions About How Neighbourhood Mechanisms tional Disadvantage in Glasgow’, Applied Geog- Affect Their Children’, Journal of Urban Affairs, raphy, 17(3): 169-92. 28(3): 201-26. Reay, D. and Lucey, H. (2000) ‘Children, School Gewirtz, S. (1998) ‘Can All Schools Be Suc- Choice and Social Differences’, Educational cessful? An Exploration of the Determinants of Studies, 26(1): 83-100. School ‘Success’’, Oxford Review of Education, 24(4): 439-57. Sampson, R.J., Morenoff, J.D. and Gannon-Row- ley, T. (2002) ‘Assessing ‘Neighborhood Effects’ Hanson Thiem, C. (2009) ‘Thinking through Social Processes and New Directions in Research‘, Education: The Geographies of Contemporary Annual Review of Sociology, 28: 443-78. Educational Restructuring’, Progress in Human Geography, 33(2): 154. Schnepf, S.V. (2007) ‘Immigrants’ Educational Disadvantage: An Examination across Ten Coun- Hattie, J.A.C. (2002) ‘Classroom Composition tries and Three Surveys’, Journal of Population and Peer Effects’, International Journal of Educa- Economics, 20(3): 527-45. tional Research, 37(5): 449-81. Thrupp, M., Lauder, H. and Robinson, T. (2002) Holloway, S., Hubbard, P., Jons, H. and Pimlott- ‘School Composition and Peer Effects’, Interna- Wilson, H. (2010) ‘Geographies of Education and tional Journal of Educational Research, 37(5): the Significance of Children, Youth and Families’, 483-504. Progress in Human Geography, in press. Waijenberg, K. (2010). Resultaten Amsterdams Leventhal, T. and Brooks-Gunn, J. (2000) ‘The Basisonderwijs 2010: Stedelijke Rapportage Neighborhoods They Live In: The Effects of Basisschooladviezen En Cito-Resultaten. Amster- Neighborhood Residence on Child and Adoles- dam: Gemeente Amsterdam, Dienst Maatschap- cent Outcomes’, Psychological Bulletin, 126(2): pelijke Ontwikkeling 309-37. Willms, J.D. (2010) ‘School Composition and Lipman, P. (2008) ‘Mixed-Income Schools and Contextual Effects on Student Outcomes’, The Housing: Advancing the Neoliberal Urban Teachers College Record, 112(4): 3-4.

Conclusion and discussion 211 & Appendix Summary Samenvatting Curriculum Vitae

Appendix: In-depth interview topic list

In November and December 2009, 16 in-depth interviews were carried out with youth who grew up in Amsterdam. Respondents were recruited through posters, email lists and flyers at local colleges, universities and community centres. All interested respondents replied to me by telephone or email to express their interest in the interview. The interviews were semi-structured and consisted of several open-ended and closed-ended questions, guided by a topic list. The interviews lasted between 1 and 2.5 hours and all respondents were given a €15 gift certificate in appreciation of their time. The following is the topic list that was used to guide the interviews. Both an English and Dutch version was used. The Dutch version is available upon request.

Introduction Hello, my name is ­­Brooke Sykes and I’m carrying out interviews for my PhD research project at the University of Amsterdam on youth, neighbourhoods and schools. The purpose of this interview is to find out more about the experiences that urban children and youth have in different social environments while growing up, particularly the school, neighbourhood, family and friendship groups. The information that I gather from these interviews will be used to improve my understanding of how these contexts interact in shaping the opportunities and constraints afforded to young people. This interview is anonymous and all information obtained is strictly confidential. No publications or reports from this project will include the real names or identifying information of any respondent. The interview will last about 1-1.5 hours. As a token of appreciation for your time, you will be given a €15 gift certificate. You can decide not to answer any question, or to stop the interview at any time. I would also like to ask if I can record the interview, as I will not be able to write down everything that you say while we speak. Do you have any questions before we begin?

I General information Year of birth, migration background

II Residential history and neighbourhood experiences 1. Can you tell me everything you remember about your neighbourhood history, starting with where you lived when you were small, until where you live today? (Use map) ––Do you recall any reasons for moving into or out of certain places?

In-depth interview topic list 215 ––Did your parents own or rent your home(s)? ––What area did you consider to be your ‘neighbourhood’ while growing up? And today, what do you consider to be your neighbourhood? (Use map) ––Where did you spend time in your neighbourhood growing up, and what kind of activities did you do there? Where did you spend time in the wider city? Doing what kind of activities? ––Can you show me on this map where your schools were located? ––How did you get to school everyday? (How long did it take and with whom did you travel?) ––Can you show me where your best friends lived, first during your primary school years? And what about your secondary school years? And today?

2. a) What do you feel are good and bad aspects about the neighbourhood(s) you grew up in? (If multiple neighbourhoods, compare). ––Can you give a story or example?

b) How would you describe the neighbourhood(s)? ––What kind of people live there? ––Did people in the neighbourhood get along or talk with each other? ––Did the children play together a lot? Was the neighbourhood safe for children? ––How many of your neighbours did you know by first and last name? ––Does the neighbourhood have a reputation or image? How do you think other people view the neighbourhood or would describe the neighbourhood? ––Where there any places in or around the neighbourhood that your parents didn’t want you to go? Where there any people in the neighbourhood that your parents didn’t want you to hang-out with? ––Has the neighbourhood changed over the years and how? ––Do you feel at home there and why?

c) Growing up, what kind of services or institutions in the neighbourhood did you use (e.g. libraries, parks or community centres)? Did you attend neighbourhood festivals or events? What kind of things did you do there? What kind of neighbourhood services do you use today?

d) Growing up, was your neighbourhood missing anything that you wished had been there?

216 Appendix e) To what extent did your family fit into the neighbourhood? How were they similar to or different from the other residents?

3. While growing up, did your family have friends, relatives or contacts in the neighbourhood, and how did they interact with them?

4. a) How did you interact with the other children in your neighbourhood?

b) How did you interact with other adults in the neighbourhood? Can you describe some occasions where you interacted with adults in the neighbourhood?

c) Did you always have the same neighbours living next to you? How often did they change?

5. Growing up, where did you know most of your friends from? Let’s start with your primary school years; then secondary school; and then today.

III Educational career and school experiences 6. Can you describe your complete school career, from primary school until today? (Describe the name, type, track level and location of your schools).

7. Do you remember why you attended those particular schools? Who made the decisions and how? ––What were important factors to consider in choosing these schools? ––How many secondary schools did you visit, and with whom? ––Were there any reasons for avoiding certain schools?

8. Can you describe the role that your parents played in your education? Can you describe the role that any other family members or other adults may have played in your education?

9. a) What kind of students attended your primary school? ––Were most students from the neighbourhood? ––Did you fit in at this school? ––What do you think the reputation of this school was (if it had one at all)?

b) And now, these same points for your secondary school – what kind of students attended your secondary school? Did you fit in at this school?

In-depth interview topic list 217 ––Did students from different class-types (Vmbo, Havo, Vwo) hang-out with each other? Did you have friends from different class-types? 10. What do you feel were good and bad aspects about these schools? Were there any things that you really liked or didn’t like about these schools?

11. What kind of student were you (e.g. did you do well in school, did you do your homework, did you enjoy school)?

IV Friends, peers, activities 12. Growing up, can you describe the kind of activities that you did outside of school? You can include organized (like sport teams) and informal (like hanging-out) activities. ––Where were they located? Who did you usually do them with?

13. Thinking about the friends you had growing up, how similar or dissimilar were your study habits and the school pathways you followed?

14. How similar would you say your school career is to your family members’? And to the people in your neighbourhood? How is it similar or different?

V Family and the home learning environment 15. Can you describe your family-life growing up? Who lived in your house? What did they do for work?

16. Can you describe the kind of activities that you did with your parents or family growing up?

17. Was it always easy to do school work at home?

VI Individual 18. What are your goals for the next few years? Where do you see yourself living?

19. Do you feel any sense of attachment to the neighbourhood(s) you grew up in, and in which way? (If you moved, which neighbourhood do you feel the

218 Appendix strongest attachment to?). Do you have any connection to other parts of the city? Ok, we’re almost finished up, this is the last section, I just have a few more specific questions.

20. Growing up in Amsterdam, either in your school, neighbourhood or other places, did you ever witness any kind of discrimination or unfair treatment, for example, because of how someone looks? Can you explain?

21. Can you describe the different ethnic/cultural backgrounds of your closest friends today?

22. What is the highest level of education of your parents and siblings?

VII Closing section Thank you very much for your time and for sharing your experiences. I have no further questions – is there anything you would like to mention before we end?

In-depth interview topic list 219

Summary 1. Introduction Intersecting questions about the effects of neighbourhood and school composition, particularly concerning social and ethnic segregation, are important and recurring topics in political and academic discussions. This dissertation sheds light on these questions by examining the educational outcomes of youth in the Netherlands, and educational inequalities more specifically, in relation to youths’ neighbourhood and school contexts. The notion of a ‘neighbourhood effect’ has received significant attention in the academic and policy world. Scholars examining neighbourhood effects investigate the links between place of residence and individual outcomes and trajectories, such as labour market status, health and wellbeing, and school career. This field of research is concerned with how much and in which ways neighbourhoods matter for individual outcomes. The underlying concern of this research is that social inequalities across neighbourhoods have implications for peoples’ social outcomes and chances in life, and thus, for the reproduction of social inequality. With many parallels to the study of neighbourhood effects, ‘school effects’ research investigates the meaning of student body composition, often in concert with other school characteristics, for such outcomes as the achievements, friendships and school careers of young people. Bringing together bodies of literature on neighbourhood effects, school effects, segregation and youth education, this book contributes to the debate on the role of the neighbourhood in shaping individual outcomes, and particularly to the understanding of the interplay between youth, neighbourhoods and schools. Although the notion of neighbourhood effects appeals to our common sense understanding that places offer different social opportunities, the story is more complex than often assumed, and adapting the concept of neighbourhood effects to policy is a contentious matter. This book consists of five separate studies that deal with different facets of the broader academic and political debate on the implications of neighbourhood and school composition. The main aims of this book are to assess the extent and nature of neighbourhood effects on youth educational outcomes; to test whether neighbourhood effects on youth are transmitted through the school context; and to work towards integrating the study of neighbourhood and school effects. More broadly, this book also aims to contribute methodologically and conceptually by assessing the usefulness of the neighbourhood effects framework for understanding the relationships between youth, their social outcomes and neighbourhood inequality. Chapters 2, 3 and 4 of this book are based on

Summary 221 quantitative analyses and empirically examine the evidence for neighbourhood effects and school effects on youth, while Chapters 5 and 6 deal with conceptual issues in the study of neighbourhood impacts and reflect more critically on the notion of neighbourhood effects. All data analyses in this book are based on a large-scale study in the Netherlands called the ‘Voortgezet Onderwijs Cohort Leerlingen – Cohort 1999’ (VOCL’99). Beginning in the school year 1999/2000, the VOCL’99 follows a cohort of students from their first year of secondary school (average age 13 years old) until they leave full-time education. From a random sample of 246 schools, 126 schools participated in the study, amounting to 19,391 students. The study presented in this book matched each student in the VOCL’99, using individual youths’ postcodes, to a neighbourhood identifier, which was then matched to neighbourhood characteristics published by Statistics Netherlands. Multilevel and cross-classified modelling techniques were used in the analysis of neighbourhood and school effects. In addition to the quantitative analyses, in-depth interviews were carried out with 16 youth who grew up in Amsterdam. The purpose of these interviews was to gain a better understanding of the interactions between youth, school and neighbourhood contexts and to explore some of the conceptual challenges in the study of neighbourhood effects on young people.

2. Neighbourhood effects on education? In Chapter 2, the educational outcomes of 18,000 youth were analysed in order to address the following research question: Can neighbourhood effects on youth educational outcomes be identified, and if so, what is the nature and extent of these effects? The findings provide support for the existence of neighbourhood effects on youth school outcomes, which operate above and beyond youths’ background characteristics, such as gender, age, parental education, family structure and ethnicity. The results indicate that youth living in economically better-off areas attain higher levels of educational achievement than those in lower-income areas. This relationship, however, is not uniform across all groups of youth; for instance, the achievement outcomes of youth from families with higher levels of socioeconomic resources appear to bear a weaker relationship to their neighbourhood conditions than those of youth with lower levels of socioeconomic resources. Thus, I conclude from these findings that the relationships between neighbourhood conditions and youth outcomes are likely to be obscured in studies that measure average neighbourhood effects across all individuals.

222 Summary These results need to be viewed in the context of several important caveats, which I discuss briefly here. Importantly, although the word ‘effects’ is used loosely in social science research to refer to statistical effects, the neighbourhood effects I find, as in those found in nearly all non-experimental quantitative analyses, are in fact empirical associations, not estimates of causal effects. Secondly, the variables used in these models (e.g. neighbourhood socioeconomic disadvantage) are constructs that serve as proxies for the social processes thought to drive effects. The mean neighbourhood income level does not have a direct effect on youth education, but processes associated with neighbourhood socioeconomic status (SES) might. Finding out which social processes drive the neighbourhood effects found in quantitative models requires ongoing work and collaboration between qualitative and quantitative researchers. I do find support for the existence of neighbourhood effects on youth educational outcomes; the next question is, why would this be so? The literature points to a number of processes thought to drive neighbourhood effects, including those tied to institutional resources and structural factors, social-interactional mechanisms and selection effects. The intervening pathway of neighbourhood effects that I focus on in this book, and discuss next, is the school.

3. Neighbourhood and school effects: Considering two contexts If the neighbourhood setting is important for young peoples’ development and outcomes, schools are arguably one of the most important reasons for this. In the theoretical literature on neighbourhood effect mechanisms, schools are posited to be one of the local institutions that contribute to place-based effects. Chapters 3 and 4 examine the extent and nature of school effects on youths’ school outcomes, and whether the school serves as a pathway of the neighbourhood effect. The results of these chapters provide support for the notion that part of the observed influence of the neighbourhood is transferred through the school context. Chapter 4 examines whether the observed relationships between neighbourhood conditions and youths’ school outcomes are explained by the schools they attend: Are neighbourhood effects on youth transferred through the school context? The results reveal that once school effects are taken into account, there are no statistically significant neighbourhood effects remaining, suggesting that the school does indeed transfer a large part of the observed neighbourhood effects. Although the original aim of these analyses was to incorporate the school into neighbourhood research by testing whether schools are a pathway of the neighbourhood effect, the story is more complex than schools simply

Summary 223 mediating neighbourhood effects. While it is reasonable to conclude that some of the influence of the neighbourhood is transferred through the school context, implying that the school is a pathway or mechanism of the neighbourhood effect, not all young people attend a school in their home neighbourhood. Although for most children their primary school is located in their home neighbourhood, this is less often the case at the secondary school level. This calls for further analysis, for example, which considers separately those who attend secondary schools in their own neighbourhood versus those who do not. A broader issue is the complexity of separating out the influence of contexts which we know to be related (e.g. the neighbourhood, school, family). Although analytically and methodologically we can separate ‘neighbourhood effects’ from ‘school effects’ (and from ‘family effects’), in reality these factors are interconnected, and thus, the actual causal pathways of these effects are bound to be intertwined. For example, a family’s residential decisions may be related to their choice of schools for their children, both of which are known to be related to family social class background. This issue has implications for how we understand neighbourhood effects, and is discussed further below. Chapter 3 examines the relationships between school characteristics and student outcomes, with a special view to the inequalities in educational achievement between ethnic and socioeconomic groups and their potential relationship to school segregation. Levels of school segregation in the Netherlands are comparatively high, for both primary and secondary education. School segregation reflects patterns of residential segregation, but is known to be reinforced by institutional features of the school system, including open school choice, family school choice decisions and academic tracking at the secondary school level. The differences in school performance between different social and ethnic groups raise questions about school conditions that might be unfavourable for students’ educational development; school segregation is seen as potentially being one of these conditions. Chapter 3 tests the effects of school ethnic and socioeconomic composition on youths’ school outcomes in Year 3 and Year 5, taking youths’ prior achievement in Year 1 into account. The results indicate a negative relationship between school ethnic composition and students’ third year achievement, but not their school position in Year 5; however, this relationship was entirely explained by differences in school socioeconomic status. Thus, as other studies have found, school SES is associated with students’ educational outcomes in the Netherlands, over and above individuals’ prior achievement, SES, and other background characteristics. Because school ethnic segregation is tied to socioeconomic segregation, segregation along both ethnic and socioeconomic lines appears to

224 Summary be relevant for students’ school outcomes. Importantly, even after taking a key set of individual background and school characteristics into account, including youths’ prior achievement levels, the analyses in Chapter 3 reveal that several minority groups perform worse relative to the native Dutch majority, and that low-SES groups perform worse than their higher-SES counterparts. The social and ethnic composition of the schools these youth attend do not account for this educational disadvantage. These performance differences are, however, more pronounced for the achievement test outcome in Year 3 than for the school position outcome in Year 5; in terms of school position in Year 5, the differences between ethnic groups are smaller and some minority groups perform better than the native Dutch group. Taken together, the results of Chapters 2, 3 and 4 all reveal persistent differences in educational achievement outcomes across individual socioeconomic and ethnic background, even after taking individual socioeconomic status, school characteristics, neighbourhood characteristics, and in some analyses, prior achievement, into account. Such systematic differences in educational outcomes are worrying, especially given that national government measures explicitly aim to redress educational inequalities. This does not necessarily imply that government interventions have been ineffective; moreover, minority ethnic groups have made steady headway in terms of levels of educational attainment and there are no reasons to believe that differences across ethnic groups in educational achievement are permanent. However, the relationships between socioeconomic and ethnic background and educational outcomes vary widely across different national contexts, thus a better understanding of what drives this variation, and how to create a more level playing field, are important and ongoing tasks for those concerned with social justice in education. From this perspective, the results of this book show that many of the standard predictors used in models of educational achievement (e.g. gender, age, ethnicity, socioeconomic status, prior achievement, school SES, school type), in addition to youths’ neighbourhood characteristics, do not fully account for observed differences in educational outcomes. Other factors are at play.

4. Neighbourhoods, their effects and social mix: The policy and research context Chapter 5 shifts gears and examines the policy context surrounding neighbourhood restructuring and neighbourhood social mixing initiatives. There is a good deal of work that connects the neighbourhood effects framework to government social mixing and poverty deconcentration initiatives, both in North America and Western Europe. It has been argued that the notion of neighbourhood

Summary 225 effects lends support to the current policy focus on promoting ‘socially mixed’ neighbourhoods and ‘cohesive communities’ as part of the answer to the problems of poverty and social inequality. However, looking more closely at how social mixing initiatives are implemented, the assumptions underlying these strategies and the research findings to date, cautions against accepting these policies uncritically. One of the key interests of Chapter 5 is the notion that the neighbourhood effects framework might work to inspire, or legitimize, neighbourhood social mixing policies. It has been suggested that the emphasis placed on neighbourhood effects has inadvertently lent theoretical and empirical weight to the idea that neighbourhoods are (at least in part) responsible for their own social problems, and hence, that solutions to these problems lie in the neighbourhood and its population mix. There is a risk that too much responsibility is assigned to neighbourhood composition, and thus to neighbourhood residents, at the expense of shifting attention away from the institutional and economic constraints that individuals face and from more fundamental determinants of poverty and inequality. While it goes without saying that researchers should always be specific and careful in their analyses and specifications, one of the main messages that emerges from Chapter 5 is that even more can be done to improve this in the field of neighbourhood effects research. A number of commentators have argued that there has been an over-reliance in neighbourhood effects research on often crude proxies, and a tendency to centre attention on behaviour which diverges most from so-called middle-class standards. There is often an implicit assumption that growing up or living in a poor neighbourhood must constitute a negative force in one’s life, even though there is a great diversity of experiences and social outcomes in even the poorest (and richest) neighbourhoods. Moreover, the forces that produce and reproduce neighbourhood social structure are given little attention in most neighbourhood effects frameworks, and thus, there is a risk of overemphasizing the role of the neighbourhood and its social composition, at the expense of obscuring wider structural forces. Understanding the effects of neighbourhoods calls for attention to how these places are produced and how neighbourhood inequalities are maintained. This would give a more balanced picture of neighbourhood effects, and would, in my view, oppose the spatial deconcentration of poverty as an effective means of promoting individual social mobility.

226 Summary 5. Above and beyond the neighbourhood: Extending the framework Chapter 6 follows from the previous chapter and explores some of the challenges in researching and understanding the meaning and role of the neighbourhood in young peoples’ everyday lives and longer-term social outcomes. While some of these challenges are the methodological difficulties inherent in trying to measure the influence of complex social contexts, they also include conceptual issues concerning the definition and interpretation of the ‘neighbourhood’ and how we conceptualize the relationships between neighbourhoods and people. I argue that neighbourhood effects research could better link up with the literature on place and space. Linking up with this literature would compel us to ask not only how neighbourhoods influence individuals, but also how individuals influence and interact with neighbourhoods – that is, how individuals come to be in particular neighbourhoods, and how they interpret, shape, draw on and give meaning to these places. The main argument of Chapter 6 is that the neighbourhood effects framework could be enriched by thinking more explicitly in terms of overlapping and reciprocal relationships running between (multiple) neighbourhood places, places of education (e.g. schools) and young people, with these relationships embedded in a wider system of institutions and socio-spatial practices. I show, through young people’s descriptive accounts, that neighbourhoods do have meaning for their everyday lives, routine activities, and likely also their longer- term outcomes, but that they are also active in choosing and interacting with the places they encounter, including their secondary schools and places within and beyond their neighbourhood. The relationship between neighbourhood and individual should be thought of as one of mutual interaction, rather than a one-way effect of neighbourhood on individual. Youths’ reports of their residential histories and interpretations of neighbourhood boundaries underscore the multiple neighbourhoods that young people inhabit and the different ways in which they define and view these places. Without taking a more holistic and relational view of the neighbourhood, or by reducing the neighbourhood to a few variables, we will miss many of the characteristics that make it a meaningful place for young people.

6. Overall conclusion Nearly no neighbourhood effects study begins with the assumption that it will uncover ‘large’ neighbourhood effects on individual outcomes. We know that individual outcomes, like educational attainment, are the result of a combination of many interrelated factors, the most important of which concern individual

Summary 227 and family characteristics. However, individuals and their families are situated in, and react to, wider neighbourhood and social structures. Overall, this study finds support for the existence of neighbourhood effects on youth educational outcomes. More precisely, youths’ educational outcomes were found to be significantly associated with characteristics of their neighbourhoods, over and above important background characteristics. However, neighbourhood characteristics do not play a direct role in youths’ school outcomes. What explains youths’ educational outcomes lies foremost at the individual level and the school level. Insofar as neighbourhoods shape school choices and school populations, which other research shows they do, they can be considered to have an indirect effect through those pathways. Neighbourhood conditions may also affect family functioning, parenting behaviour, and individual interests, which, in turn, may affect individual school outcomes. Thus, neighbourhood effects on young people’s educational outcomes can best be thought of as indirect and incidental. The extent to which a unique or independent neighbourhood effect can be accurately identified is questionable. Where young people live is related to the friends and peer groups they have while growing up, the schools they attend, and their families’ social class background, and thus, many facets of a young person’s social world are intertwined. This suggests the need to broaden the neighbourhood effects framework to better capture the interactions between youth and the multiple places that they inhabit. The results of this book provide many reasons to look further into the influence of neighbourhoods, and the interaction between neighbourhoods, schools and youth, but ideally this should be conducted with an awareness of the interconnectedness among youth, their current and past neighbourhoods, schools, homes and the other places they encounter.

7. Suggestions for future research This dissertation has resulted in a number of ideas and suggestions for future research, some of them already mentioned above. Above all, I suggest two ways in which thinking about and researching neighbourhood effects could be complemented and extended. First, I suggest that it is necessary to be more conscious of how neighbourhood space and neighbourhood social structure are produced and maintained. There is a vast geographical literature on the (re)production of uneven geographies; in my view, this literature helps to put the notion of neighbourhood effects into perspective. While inequalities across neighbourhoods have implications for individuals, the production of these spatial inequalities is not an arbitrary matter. Furthermore, the underlying causes of ‘neighbourhood effects’ do not typically lie in the neighbourhood

228 Summary itself. Thus, one could ask, for example, which social and structural relations underpin neighbourhood segregation? What do socio-spatial inequalities and neighbourhood effects reveal about the political, economic, social and cultural processes in which they are embedded? The production of neighbourhood geographies is also of direct importance to the issue of selection effects (or selection bias) in neighbourhood effects research. It is widely recognized that people do not come to live in neighbourhoods through random processes (and likewise, that children and youth do not come to attend certain schools through random processes). To understand the impact of place, it is important to view this selection as a fundamental social process in itself, and something of substantive interest to neighbourhood effects and to how neighbourhood structure is continuously made and remade. Secondly, I advocate a better consciousness of the mutuality or reciprocal relations between people and the multiple places they inhabit and spend time in, including the neighbourhood. Although the neighbourhood is seen to affect individuals, how individuals shape the neighbourhood tends to be given little attention in neighbourhood effects research; the issue is widely acknowledged, yet still tends to be underappreciated. While this mutuality does indeed pose a significant challenge to measuring the ‘effects of neighbourhoods’, it suggests that we might look at the question of neighbourhood effects from a different perspective: not only how neighbourhoods affect people, but also how people affect neighbourhoods, including how they choose, are selected into, excluded from, shape, give meaning to, and interact with neighbourhoods. Taken together, these two interrelated points about neighbourhood selection/production and simultaneity/mutuality encourage neighbourhood effects researchers to broaden the lens through which neighbourhoods and their relationships with people are viewed, and to examine both sides of the person–place relationship. Further integrating qualitative and quantitative knowledge and research methods, and adopting a more place-sensitive approach to the study of neighbourhoods and people, will be important steps in moving forward in the field of neighbourhood research.

Summary 229

Samenvatting 1. Inleiding Vragen over de effecten van de samenstelling van buurten en scholen, in het bijzonder de invloed van de sociale en etnische segregatie binnen deze contexten, zijn belangrijke en terugkerende onderwerpen in politieke en academische discussies. Dit proefschrift werpt licht op deze vragen door te onderzoeken of de onderwijsprestaties van jongeren in Nederland, en onderwijsongelijkheden in het bijzonder, gerelateerd zijn aan de buurt- en schoolcontexten van deze jongeren. Het idee van een ‘buurteffect’ geniet aanzienlijke aandacht in de wereld van academische onderzoekers en beleidsmakers. Wetenschappers die onderzoek doen naar buurteffecten, bestuderen de verbanden tussen de woonplaats van een persoon enerzijds en diens individuele positie en ontwikkelingsmogelijkheden anderzijds, zoals de arbeidsmarktpositie, gezondheid, welzijn en schoolcarrière. Kortom, dit onderzoeksgebied houdt zich bezig met de vraag in welke mate en op welke manieren buurten van belang zijn voor de kansen van individuen. Het achterliggende idee is dat de spreiding van sociale ongelijkheden over buurten implicaties heeft voor het sociale succes van mensen en hun kansen in het leven, en daarmee voor de reproductie van sociale ongelijkheid. Op eenzelfde wijze richt het onderzoek naar ‘schooleffecten’ zich op de betekenis van de samenstelling van schoolpopulaties voor schoolprestaties, vriendschappen en schoolloopbanen van jonge mensen, dit vaak naast andere schoolkenmerken. Door het samenbrengen van literatuur vanuit verschillende disciplines over buurteffecten, schooleffecten, segregatie en onderwijs aan jongeren, draagt dit boek bij aan het debat over de betekenis van de buurt voor individuele ontwikkeling, en in het bijzonder aan de wijze waarop jeugd, buurten en scholen met elkaar samenhangen en invloed uitoefenen op de positie en kansen van jongeren. Hoewel het idee van buurteffecten logisch lijkt in de zin dat plaatsen verschillende sociale kansen bieden, is de werkelijkheid complexer dan vaak wordt aangenomen. Dit betekent ook dat in het beleid voorzichtig moet worden omgegaan met de toepassing van het concept ‘buurteffect’. Dit boek bestaat uit vijf studies die zich bezighouden met verschillende aspecten van het bredere academische en politieke debat over de implicaties van de samenstelling van buurten en scholen voorindividuele schoolprestaties. De hoofddoelstellingen van dit boek zijn het bepalen van de omvang en aard van buurteffecten op de schoolprestaties van jongeren; het testen of gevonden buurteffecten via de schoolcontext verlopen (de vraag of zij via de school worden overgebracht); bij te dragen aan een verdere integratie van de studies naar buurt– en schooleffecten; en bijdragen aan de methodologische en conceptuele

Samenvatting 231 kennis op bovengenoemd gebied, door de bruikbaarheid te beoordelen van het analyseraamwerk dat wordt gebruikt om de relaties tussen jeugd, hun sociale positie en buurtongelijkheid te onderzoeken. Hoofdstukken 2, 3 en 4 van dit boek zijn gebaseerd op kwantitatieve analyses en onderzoeken het empirische bewijs voor het bestaan van buurt- en schooleffecten voor jongeren. Hoofdstukken 5 en 6 behandelen conceptuele vraagstukken in het buurteffectonderzoek en gaan kritisch in op het idee van buurteffecten. Alle data-analyses in dit boek zijn gebaseerd op een in Nederland uitgevoerd grootschalig onderzoek, genaamd ‘Voortgezet Onderwijs Cohort Leerlingen – Cohort 1999’ (VOCL’99). Dit cohort volgt vanaf schooljaar 1999/2000 een grote groep leerlingen vanaf hun eerste jaar (gemiddelde leeftijd 13 jaar) op de middelbare school totdat zij het voltijd onderwijs hebben verlaten. Er is een aselecte steekproef getrokken van 246 scholen. Daarvan hebben 126 scholen aan het cohort deelgenomen, met in totaal 19.391 leerlingen. Door middel van de postcodes van de respondenten is elke leerling in het cohort gekoppeld aan een buurtcode, die vervolgens is gekoppeld aan de buurtkenmerken die gepubliceerd zijn door het Centraal Bureau van de Statistiek. Bij de analyse en modellering van buurt– en schooleffecten zijn multilevel en cross-classified technieken gebruikt. In aanvulling op de kwantitatieve analyses zijn 16 diepte-interviews gehouden met jongeren die in Amsterdam opgroeiden. Het doel van deze interviews was om beter grip te krijgen op de wisselwerking die bestaat tussen jeugd, school en buurtcontexten, en om een aantal van de conceptuele vragen te verkennen die leven binnen de studie van buurteffecten op jonge mensen.

2. Buurteffecten op scholing? In Hoofdstuk 2 zijn de onderwijsprestaties van 18.000 jongeren geanalyseerd om de volgende onderzoeksvraag te beantwoorden: Kunnen er buurteffecten op de schoolprestaties van jongeren worden vastgesteld, en zo ja, wat is de aard en omvang van deze effecten? De resultaten leveren een onderbouwing voor het bestaan van bescheiden buurteffecten op de schoolprestaties van jongeren, die bestaan naast effecten van achtergrondkenmerken van jongeren, zoals geslacht, leeftijd, opleiding van de ouders, familiestructuur en etniciteit. Jongeren die in meer welgestelde gebieden wonen, bereiken een hoger onderwijsniveau dan degenen die in gebieden met relatief veel lage inkomens wonen. Deze relatie is echter niet hetzelfde voor alle groepen jongeren. Zo blijken de schoolprestaties van jongeren uit huishoudens van hogere sociaal-economische klasse een zwakkere relatie te hebben met buurtkenmerken dan die van jongeren uit huishoudens van een lagere sociaal-economische klasse. Een belangrijke conclusie is daarom dat in studies waarin alleen de gemiddelde buurteffecten worden gemeten, sommige

232 Samenvatting relaties tussen buurtkenmerken en de effecten daarvan op jongeren verborgen blijven. Er dient een aantal kanttekeningen bij deze onderzoeksresultaten te worden geplaatst. Het is allereerst belangrijk om stil te staan bij het gegeven dat hoewel in onderzoek het woord ‘effecten’ losjes wordt gebruikt om naar statistische verbanden te verwijzen, de ‘buurteffecten’ die ik heb gevonden, en zoals die in vrijwel alle non-experimentele kwantitatieve analyses worden gevonden, in feite empirische relaties zijn, en dus geen schattingen van causale effecten. Ten tweede zijn de variabelen die in deze modellen worden gebruikt (bijvoorbeeld de ‘sociaal-economische achterstand van de buurt’) constructen die de sociale processen trachten te meten waarvan gedacht wordt dat ze bepaalde effecten voortbrengen. Het gemiddelde inkomensniveau van de buurt heeft geen direct effect op de schoolprestaties van jongeren, maar processen die gerelateerd zijn aan de sociaal-economische status (SES) van de buurt zouden dat wel kunnen hebben. Welke sociale processen nu precies schuilgaan achter de in kwantitatieve modellen gevonden buurteffecten, is een belangrijke vraag voor het onderzoek naar buurteffecten, die samenwerking vereist tussen kwalitatieve en kwantitatieve onderzoekers. In het eerste deel van mijn onderzoek heb ik dus een onderbouwing gevonden voor het bestaan van buurteffecten op de onderwijsprestaties van jongeren. De volgende vraag is, waarom dit zo zou zijn. De literatuur verwijst naar een aantal processen waarvan wordt aangenomen dat ze buurteffecten voortbrengen, waaronder processen die verbonden zijn met institutionele hulpbronnen/ voorzieningen en structurele factoren, mechanismen van sociaal handelen en selectie-effecten. Het interveniërende pad waarlangs buurteffecten zich kunnen voordoen, en waarop ik mij in de rest van dit boek heb geconcentreerd, is de school.

3. Buurt- en schooleffecten: Het beschouwen van twee contexten Als de buurt van belang is voor de ontwikkeling en prestaties van jongeren, dan is de school hoogstwaarschijnlijk een van de belangrijkste redenen daarvoor. In de theoretische literatuur over mechanismen van het buurteffect worden scholen beschouwd als een van de lokale instituties die bijdragen aan plaatsgebonden effecten. In de hoofdstukken 3 en 4 wordt ingegaan op de aard en omvang van schooleffecten op de schoolprestaties van jongeren, en of de school functioneert als een pad waarlangs buurteffecten plaatsvinden. De resultaten van deze hoofdstukken onderbouwen de gedachte dat een deel van de waargenomen invloed van de buurt inderdaad via de schoolcontext wordt overgebracht.

Samenvatting 233 Hoofdstuk 4 onderzoekt of de waargenomen relaties tussen buurtkenmerken en schoolprestaties van jongeren kunnen worden verklaard door de scholen die zij bezoeken: Worden buurteffecten via de schoolomgeving op jongeren overgedragen? De resultaten wijzen uit dat, wanneer er rekening wordt gehouden met schooleffecten, er geen statistisch significante buurteffecten overblijven. Dit suggereert dat de school inderdaad een belangrijk deel van de waargenomen buurteffecten voor haar rekening neemt. Het verhaal zit echter complexer in elkaar dan dat scholen eenvoudigweg buurteffecten overdragen. Hoewel geconstateerd is dat een deel van de invloed van de buurt via de schoolcontext verloopt ­– hetgeen impliceert dat de school een tussenliggend pad of mechanisme van het buurteffect is – is het ook een feit dat niet alle jongeren naar een school in hun eigen buurt gaan. Bevindt de lagere school voor veel kinderen zich nog wel in de eigen buurt, dit is minder vaak het geval voor de middelbare school. Dit vraagt om een verdere analyse, bijvoorbeeld het afzonderlijk beschouwen van degenen die binnen de eigen buurt naar school gaan en degenen die dat niet doen. Een meer algemene kwestie is de complexiteit van het uit elkaar trekken van de invloed van contexten waarvan we weten dat ze aan elkaar verbonden zijn (bijv. de buurt, school, gezin). Hoewel we ‘buurteffecten’ en ‘schooleffecten’ analytisch en methodologisch van elkaar kunnen scheiden (evenals van ‘gezinseffecten’), zijn deze factoren in werkelijkheid onderling verstrengeld, en zijn de causale paden van deze effecten eveneens sterk met elkaar verweven. Zo kan de keuze van een woonomgeving van een gezin samenhangen met de schoolkeuzen voor hun kinderen, die beide weer gerelateerd kunnen zijn aan de sociale klasse van het gezin. Deze kwestie heeft implicaties voor ons begrip van buurteffecten. Hieronder ga ik daar nader op in. Hoofdstuk 3 behandelt de relatie tussen schoolkenmerken en prestaties van leerlingen, met bijzondere aandacht voor de ongelijkheden in onderwijsprestaties tussen etnische en sociaal-economische groepen en de potentiële relatie met schoolsegregatie. De mate van schoolsegregatie is in Nederland relatief hoog, zowel voor het basisonderwijs als voor het voortgezet onderwijs. Schoolsegregatie weerspiegelt patronen van residentiële segregatie, maar het is bekend dat deze versterkt wordt door institutionele kenmerken van het schoolsysteem, waaronder de vrije schoolkeuze, de schoolkeuzen van gezinnen en het uitsplitsen van leerlingen naar leervermogen in het voortgezet onderwijs. De vraag is of verschillen in schoolprestatie tussen verschillende sociale en etnische groepen te herleiden zijn tot schoolomstandigheden die nadelig zijn voor de onderwijskansen van leerlingen, waarbij schoolsegregatie een van de potentieel nadelige omstandigheden is.

234 Samenvatting In hoofdstuk 3 worden de effecten getoetst van de etnische en sociaal- economische samenstelling van de school op de schoolprestaties van jongeren in jaar 3 en jaar 5, waarbij rekening wordt gehouden met de eerdere resultaten in jaar 1. De resultaten wijzen op een negatief verband tussen de etnische samenstelling van de school en de onderwijsprestaties van leerlingen in hun derde jaar, maar niet hun positie in het vijfde jaar. Dit verband wordt echter volledig verklaard door verschillen in de sociaal-economische status (SES) van de school. Zoals andere studies eerder hebben aangetoond, is de gemiddelde school-SES in Nederland gerelateerd aan de prestaties van de leerlingen, ook als rekening wordt gehouden met eerdere prestaties, SES en andere achtergrondkenmerken. Omdat etnische schoolsegregatie gerelateerd is aan sociaal-economische segregatie, blijkt segregatie langs etnische en sociaal-economische lijnen relevant te zijn voor de onderwijsprestaties van leerlingen. Zelfs als rekening wordt gehouden met een aantal achtergrond- en schoolkenmerken, en met het eerdere prestatieniveau, laten de analyses in hoofdstuk 3 zien dat verschillende minderheidsgroepen in vergelijking met de autochtone Nederlandse meerderheid slechter presteren, en dat groepen met een lagere SES slechter presteren dan hun hogere SES tegenhangers. De sociale en etnische samenstelling van de scholen die door deze jongeren worden bezocht, vormen hiervoor geen verklaring. Deze prestatieverschillen zijn echter meer uitgesproken op de toetsen in het derde jaar dan voor de onderwijspositie in het vijfde jaar. In termen van de onderwijspositie in het vijfde jaar zijn de verschillen tussen etnische groepen kleiner en presteren sommige minderheden beter dan de Nederlandse leerlingen. De resultaten van de hoofdstukken 2, 3 en 4 wijzen op persistente verschillen in onderwijsprestaties naar individuele sociaal-economische en etnische achtergronden, zelfs als rekening wordt gehouden met de individuele sociaal- economische status, schoolkenmerken, buurtkenmerken en, in een aantal analyses, eerdere prestaties. Zulke systematische verschillen in onderwijsprestaties zijn zorgwekkend, vooral gezien de maatregelen van nationale overheden die er uitdrukkelijk op zijn gericht om onderwijsongelijkheden weg te nemen. Dit houdt niet noodzakelijkerwijs in dat het overheidsingrijpen niet effectief is geweest; etnische minderheidsgroepen hebben gestage vorderingen gemaakt in termen van opleidingsniveau en er zijn geen redenen om aan te nemen dat verschillen in onderwijsprestaties blijvend zijn. De relatie tussen sociaal-economische en etnische achtergrond en onderwijsprestaties varieert overigens sterk tussen verschillende nationale contexten. Het is van groot belang om deze variatie beter te begrijpen, zodat meer gelijke speelvelden kunnen worden gecreëerd. Dit zijn belangrijke taken voor degenen die zich bezig houden met sociale rechtvaardigheid in het

Samenvatting 235 onderwijs. De resultaten van dit boek laten zien dat veel van de verklarende variabelen die standaard worden toegepast in modellen voor schoolprestaties (bijvoorbeeld. geslacht, leeftijd, etniciteit, sociaal-economische status, eerdere prestaties, school-SES, schooltype), naast de buurtkenmerken, geen volledige verklaring geven voor de waargenomen verschillen in onderwijsprestaties. Er zijn dus andere factoren in het spel.

4. Buurten, hun effecten en de sociale mix: de beleids– en onderzoekscontext Hoofdstuk 5 maakt een sprong en onderzoekt de beleidscontext van het herstructureren van buurten en initiatieven voor een sociale mix in buurten. In veel onderzoek wordt de link gelegd tussen het verklarend raamwerk van buurteffecten en het door de overheid uitgevoerde beleid van ‘sociale mix’ en andere initiatieven op het gebied van deconcentratie van armoede, zoals dat gebeurt zowel in Noord-Amerika als in West-Europa. Sommigen beweren dat het idee van buurteffecten een legitimatie biedt voor de huidige beleidsfocus, gericht op het bevorderen van ‘sociaal gemengde’ buurten en ‘samenhangende gemeenschappen’ als deel van het antwoord op de problemen van armoede en sociale ongelijkheid. Kijkt men echter nauwkeuriger naar hoe de initiatieven voor sociale mix worden geïmplementeerd, naar de aannamen van deze strategieën en naar de onderzoeksbevindingen tot op heden, dan is een waarschuwing tegen het kritiekloos accepteren van zulk beleid op zijn plaats. Er wordt wel beweerd dat de nadruk op buurteffecten een onbedoelde theoretische en empirische legitimatie heeft gevormd voor het idee dat buurten (ten minste ten dele) zelf verantwoordelijk zijn voor hun eigen sociale problemen, en dat de oplossingen voor deze problemen dus in de buurt en zijn bevolkingssamenstelling liggen. Het risico bestaat dat te veel belang wordt toegekend aan de buurtsamenstelling, en dus aan buurtbewoners. Hierdoor wordt de aandacht afgeleid van de institutionele en economische beperkingen waar individuen mee te maken hebben, alsmede van meer fundamentele determinanten van armoede en ongelijkheid. Hoewel het overbodig is te zeggen dat onderzoekers specifiek dienen te zijn en voorzichtig in hun analyses en specificaties, is een van de belangrijkste boodschappen van hoofdstuk 5 dat dit in nog sterkere mate geldt voor het onderzoek naar buurteffecten. Zo stellen critici dat er in het onderzoek naar buurteffecten een te groot vertrouwen bestaat in veelal ruwe benaderingen voor sociale processen, en dat er te veel aandacht is voor gedrag dat afwijkt van de zogenaamde middenklasse-standaarden. Vaak wordt impliciet aangenomen dat het opgroeien of wonen in een arme buurt sowieso een negatieve invloed heeft,

236 Samenvatting ook al bestaat er zelfs in de armste (en rijkste) buurten een grote diversiteit aan ervaringen en sociale uikomsten. Bovendien wordt er in de meeste studies naar buurteffecten weinig aandacht geschonken aan de factoren die de sociale structuur van de buurt tot stand brengen en reproduceren. Er is dus een gevaar dat men te sterk de nadruk legt op de rol van de buurt en zijn sociale samenstelling, terwijl bredere structurele krachten verborgen blijven. Voor het begrip van buurteffecten is het noodzakelijk aandacht te hebben voor hoe deze plaatsen tot stand komen en hoe buurtongelijkheden in stand worden gehouden. Dan kan een meer evenwichtig beeld van buurteffecten worden gegeven. Dit zou kunnen leiden tot een stellingname tegen ruimtelijke deconcentratie van armoede als een effectief middel om individuele sociale mobiliteit te bevorderen.

5. Verder dan de buurt: naar een ruimer kader Een logisch vervolg van deze discussie is neergelegd in hoofdstuk 6. Daarin wordt een aantal van uitdagingen aan de orde gesteld die verbonden zijn aan de betekenis van de buurt in het dagelijkse leven van jongeren en de sociale implicaties daarvan op langere termijn. Terwijl een aantal van deze uitdagingen de methodologische moeilijkheden betreffen die inherent zijn aan de poging om de invloed van complexe sociale contexten te meten, bevatten zij ook conceptuele kwesties die te maken hebben met de definitie en interpretatie van de ‘buurt’ en hoe we de relatie tussen buurten en mensen conceptualiseren. Naar mijn mening zou het buurteffectenonderzoek een betere aansluiting moeten vinden bij de literatuur over plaats en ruimte. Een aansluiting bij deze literatuur zou ons ertoe moeten brengen om niet alleen te vragen hoe buurten individuen beïnvloeden, maar ook hoe individuen invloed uitoefenen op en in wisselwerking staan met buurten – dat wil zeggen, hoe individuen in bepaalde buurten terecht komen en hoe zij deze plekken interpreteren, vormgeven, ervan gebruikmaken en betekenis geven. Het hoofdargument van hoofdstuk 6 is dat het buurteffectenonderzoek zou kunnen worden verrijkt door meer expliciet te denken in termen van overlappende en wederzijdse relaties die lopen tussen (meervoudige) buurtomgevingen, onderwijsomgevingen (in casu scholen) en jonge mensen, waarbij deze relaties ingebed liggen in een omvangrijker systeem van instituties en sociaal-ruimtelijk handelen. De interviews met jongeren laten zien dat buurten wel degelijk een betekenis hebben voor hun dagelijks leven, hun alledaagse bezigheden en waarschijnlijk ook voor hun perspectieven op de lange termijn. Maar ook dat ze actief zijn in het kiezen van hun plaatsen, waaronder hun school en andere plaatsen binnen en buiten hun buurt en hoe zij zich gedragen in die plaatsen. De relatie tussen buurt en individu moet eerder worden gezien als een wederzijdse interactie dan

Samenvatting 237 als een unilateraal effect van de buurt op het individu. Verhalen van jongeren over hun woongeschiedenis en hun interpretaties van buurtgrenzen onderstrepen de meervoudigheid van buurten die jonge mensen bewonen en de verschillende manieren waarop zij deze plaatsen definiëren en beschouwen. Zonder een meer holistische en relationele visie op de buurt, of door het reduceren van de buurt tot slechts enkele variabelen, zullen we veel missen van hetgene dat een plek betekenisvol maakt voor jongeren.

6. Algemene conclusie Vrijwel geen enkele studie naar buurteffecten begint met een a priori aanname dat deze ‘grote’ buurteffecten op individuele prestaties zal blootleggen. We weten dat persoonlijke prestaties, zoals het bereiken van een bepaald opleidingsniveau, het resultaat zijn van een combinatie van vele met elkaar verweven factoren, waarvan de persoonlijke en gezinskenmerken de belangrijkste zijn. Individuen en hun huishoudens bevinden zich echter binnen een bredere leefomgeving en sociale structuren, en reageren daarop. Globaal genomen vindt deze studie onderbouwing voor het bestaan van buurteffecten op de schoolprestaties van jongeren. Meer specifiek hangen de schoolprestaties van jongeren significant samen met kenmerken van hun buurten, ook nadat rekening is gehouden met belangrijke achtergrondkenmerken. Echter, buurtkenmerken spelen geen directe rol in de schoolprestaties van jongeren. Wat de schoolprestaties van jongeren verklaart, ligt allereerst op het individuele vlak en het schoolniveau. Voor zover buurten verbonden zijn met schoolkeuzen en schoolpopulaties – waarvan onderzoek aantoont dat ze dat zijn – kunnen ze worden beschouwd als een indirect effect, lopend via genoemde paden. Buurten kunnen ook invloed hebben op het functioneren van gezinnen, gedrag van ouders, en individuele belangen, welke op hun beurt effect kunnen hebben op schoolprestaties. Derhalve kunnen buurteffecten op de onderwijsprestaties van jonge mensen het best worden beschouwd als indirect en bijkomstig. Het is twijfelachtig of kan worden vastgesteld of er sprake is van een uniek of onafhankelijk buurteffect. Waar iemand woont, is gerelateerd aan de vrienden en groepsgenoten die men heeft terwijl men opgroeit, aan de scholen die men bezoekt, en aan de sociale klasse-achtergrond van hun familie. Op die manier zijn vele aspecten van de sociale wereld van jongeren met elkaar vervlochten. Dit geeft de noodzaak aan om het kader van buurteffectstudies te verbreden om zo de interacties tussen jongeren en de meervoudige plaatsen die zij bewonen beter te kunnen vaststellen. De uitkomsten van dit boek leveren vele redenen op om verder te kijken naar de invloed van buurten, en de wisselwerking tussen buurten, scholen en jeugd. Idealiter zou dit moeten worden uitgevoerd met een besef van

238 Samenvatting de onderlinge verbondenheid tussen jongeren, hun huidige en vroegere buurten, hun scholen, woningen en de andere plaatsen waarin zij zich begeven.

7. Suggesties voor toekomstig onderzoek Dit proefschrift heeft een aantal ideeën en suggesties voor toekomstig onderzoek opgeleverd, waarvan een aantal hierboven is genoemd. In zijn algemeenheid stel ik twee manieren voor waarop het denken over en het onderzoek naar buurteffecten zou kunnen worden gecomplementeerd en uitgebreid. Ten eerste is het nodig ons meer bewust te zijn van hoe buurten en de sociale structuur van de buurt tot stand komen en in stand worden gehouden. Er bestaat een uitgebreide geografische literatuur over de (re)productie van ruimtelijke ongelijkheid; en naar mijn mening helpt deze literatuur het idee van buurteffecten meer in perspectief te zetten. Hoewel ongelijkheden tussen buurten implicaties hebben voor individuen, is de productie van deze ruimtelijke ongelijkheden geen arbitraire zaak. De onderliggende oorzaken van ‘buurteffecten’ liggen niet specifiek in de buurt. Het is meer de vraag welke sociale en structurele relaties bepalend zijn voor de ruimtelijke segregatie. Wat vertellen sociaal-ruimtelijke ongelijkheden en buurteffecten ons over de politieke, economische, sociale en culturele processen waarin zij verankerd liggen? De productie van bepaalde buurten is ook van direct belang voor de kwestie van selectie-effecten (of ‘selection bias’) in onderzoek naar buurteffecten. Het wordt vrij algemeen erkend dat mensen niet door willekeurige processen in een buurt komen te wonen (en ook dat kinderen en jongeren niet door willekeurige processen op bepaalde scholen terechtkomen). Om de invloed van plaats te begrijpen, is het belangrijk een dergelijke ‘selectie’ te beschouwen als een fundamenteel op zich zelf staand sociaal proces en als iets dat van substantieel belang is voor buurteffecten, en voor de wijze waarop de structuur van de buurt voortdurend wordt ge(re)produceerd. Ten tweede bepleit ik een beter besef van de gemeenschappelijke of wederzijdse relaties tussen mensen en de meervoudige plaatsen die zij bewonen en waarin zij hun tijd doorbrengen, waaronder de buurt. Hoewel blijkt dat de buurt individuen beïnvloedt, wordt er in het onderzoek naar buurteffecten weinig aandacht gegeven aan hoe individuen de buurt vormgeven. Deze kwestie wordt wel erkend in de literatuur over buurteffecten, maar wordt nog steeds ondergewaardeerd. Hoewel de wederkerigheid een enorme uitdaging vormt om de ‘effecten van buurten’ te meten, biedt het tegelijkertijd een ander perspectief op buurteffecten. Namelijk: niet alleen hoe buurten mensen beïnvloeden, maar ook hoe mensen buurten beïnvloeden, inclusief hoe zij kiezen, geselecteerd worden, worden buitengesloten van, vormgeven aan, betekenis geven aan, en in wisselwerking staan met buurten. Samen moedigen deze twee met elkaar

Samenvatting 239 verbonden punten over buurtkeuze/productie en gelijktijdigheid/wederkerigheid onderzoekers van buurteffecten aan om de lens, waardoor zij naar buurten en hun verhoudingen tot mensen kijken, wijder open te zetten en beide kanten van de persoon–plaatsrelatie te onderzoeken. Verdere integratie van kwalitatieve en kwantitatieve kennis en onderzoeksmethoden, en de toepassing van een plaats-gevoelige benadering van de bestudering van buurten en mensen, vormen belangrijke stappen in de vooruitgang van het buurt(effect)onderzoek.

240 Samenvatting