Social Capital and Inequality in Singapore

SOCIAL CAPITAL AND INEQUALITY IN SINGAPORE

Vincent Kynn Hong Chua

A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy Department of Sociology University of Toronto

Social Capital and Inequality in Singapore

Vincent Chua

Degree of Doctor of Philosophy

Department of Sociology University of Toronto

2010

Abstract

Written as three publishable papers, this dissertation examines the sources of several forms of social capital in Singapore, and the effects of social capital on occupational success.

Using representative survey data from Singapore, these papers make several important theoretical contributions:

The first paper examines how and why categorical forms of stratification such as gender and ethnicity tend to produce distinctive forms of network inequalities: for example, whereas Chinese (relative to Malays and Indians) tend to have greater access to well- educated, wealthy, Chinese and weak tie social capital (but not non-kin), men (relative to women) tend to have greater access to men, non-kin and weak ties (but not well- educated, wealthy and Chinese). The key to understanding such distinctive patterns of network inequalities (by gender and ethnicity) is to understand the distinctive ways in

which gender and ethnic groups are distributed in routine organizations such as schools, paid work and voluntary associations.

The second paper examines the significance of personal contacts in job searches, in the context of Singapore’s meritocratic system. I show that in certain sectors such as the state bureaucracy, social networking brings no distinct advantages as appointments are made exclusively on the basis of the credentials of the candidates. Thus, personal contacts are not always useful, especially in labour markets that rely heavily on the signalling role of academic credentials to match people to jobs. In contrast, personal contacts are more useful among less qualified job searches in the private sector.

The third paper shows that while job contacts (i.e. ‘mobilized’ social capital) may not always pay off in meritocratic labour markets, ‘accessed’ social capital remains extremely important. The leveraging power of social capital in meritocratic markets is not the active mobilization of job contacts per se, but more subtly, the result of embedded social resources such as knowing many university graduates and wealthy people.

Together, these papers illustrate how socio-structural factors such as meritocracy, gender and racialization form important predictors of the distribution, role and value of social capital in everyday life and labour markets.

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“The life of an individual cannot be adequately understood without references to the institutions within which his biography is enacted.”

C. Wright Mills

ACKNOWLEDGEMENTS

I owe a unique debt of gratitude to the chair of my dissertation committee: Professor Bonnie Erickson, who introduced me to the fascinating world of social capital and through her close mentoring, helped me be a better researcher. I have gained much from her intellectual agility and her very incisive feedback of my work.

I am indebted to Professor Barry Wellman, who imparted many important lessons concerning the art (and science) of scholarly writing and who gave me several opportunities to co-author book chapters and journal publications. I have learned much from these collaborations and will strive to be just as supportive of my own students in the future.

My sincere thanks go to Professor Zaheer Baber, who was a continual source of friendship and support during my PhD years. It is interesting how our paths have converged twice -– first in Singapore (during Sociology 101) and later in Toronto.

I am grateful for the support of Professor Eric Fong and Professor Bob Andersen, both of whom kindly agreed to be part of this dissertation committee.

As statistical analyses are an integral part of this dissertation, I acknowledge my mentors in social statistics: Professor Ann Sorenson and Professor Blair Wheaton, who through their excellent teaching, enlightened my understanding concerning the role of ‘numbers’ in Sociology. My active interest in teaching social statistics today is a direct result of being in those classes.

I thank Professor John Myles and Professor Shyon Baumann for being so supportive of my work during the doctoral research practicum. Their generous comments and insights helped me win the Daniel Grafton Hill Best Graduate Paper Prize, but more importantly, they taught me how to write and angle a scholarly paper. This paper was subsequently accepted for publication in Social Networks .

Deep thanks go to Jeannette Wright, our indispensible graduate coordinator, who during the five years, managed my file, and made sure that I (along with other graduate students) met our administrative deadlines. I thank Kai-Lii Veer, our new graduate coordinator, for her additional administrative help with the PhD oral defense.

Many friends in graduate school have made my journey a memorable one. Omar Faruque and Jing Shen were reliable dinner companions. We talked about many things, often in melodramatic terms: the chaos (but homeliness) of Bangladesh, the vibrancy (but messiness) of contemporary China, the neatness (but restrictions) of Singapore and of course, the enviable “quality of life” in Canada.

Chia Yeow Tong, a PhD student at OISE and fellow Singaporean, taught me the value of an entrepreneurial outlook amid seemingly insurmountable challenges.

My office mates, Rochelle Coté and Phillipa Chong, were supportive co-runners in the PhD journey. Rochelle (together with Jennifer Kayahara) organized dissertation brainstorming sessions. Phillipa always made sure we had our afternoon tea and arranged dinners and parties on several occasions, the most memorable of which was (of course) the post PhD defense and farewell party she kindly put together for me.

A number of people including my committee read all or parts of the manuscript: John Myles, Shyon Baumann, Paul Glavin, Deanna Pikkov, Mark Easton, Bader Araj, Naoko Shida, Roxanna Waterson, Lim Chih Yang, Lim Weida, Julia Wong, Stephen Appold and Elizabeth Thompson. Their comments were very valuable.

I thank Paul Glavin and Paul Armstrong for being such caring colleagues, as well as Lisa Kaida and Stella Park for providing such strong peer support throughout the years. I thank members of the Critical Sociology Book Review Collective, in particular Nadine Blumer for steering the collective, and for allowing me to contribute ‘Notebooks’. To the rest of the Collective: Michal Bodemann, Zaheer Baber, Paul Armstrong, Norah

MacHendrick, Tara Hahmann, Sarah Knudson and Agata Piekosz, I will certainly miss our meetings and friendship.

NETLAB has become an important part of my life: besides Professor Barry Wellman, I thank, in particular, Julia Madej and Natalie Zinko for their partnership in our writing projects.

Rubens Rahim and Stacey Westwell gave me warm hospitality both in Toronto and Vancouver. They were always welcoming and concerned about my welfare and progress.

Danny and Lauren Teh were very close companions. The dinners (with Peter and Halle) were like family gatherings.

The Salvadors (Joseph, Evelyn, and Mamy) were very warm people. The Wongs: Uncle Wong, Aunty Emily, Fiona, Nicholas, Aaron and Camille were, like the Tehs and Salvadors, very gracious.

Roy Abraham was a close friend and confidant. Victor and Sue Kasenda, Tracy Qin, Zhao Yanfei, Grace So, Kim Larsen and Suzyo Chilongo were close buddies.

I thank the National University of Singapore, in particular Professors Lian Kwen Fee, Hing Ai Yun, Paulin Straughan, Tong Chee Kiong, Ho Kong Chong, Tan Ern Ser and Chua Beng Huat, for believing I could get the job done, and for their encouragements along the way.

This dissertation is dedicated to my parents, Chua Cheow Hwa and Lee Kwee Mildred. This PhD is a reflection of their unconditional love all these years.

My eldest brother, Justin Chua and sister-in-law, Lynn Tan (and their children Joshua and Ariane) were especially kind. They were like angels guiding me, paving my journey, turning my PhD from crucible to sweet waters.

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My second brother Leonard Chua and his wife Tricilia Tang (and their children Josthan and Tenessa) were very supportive. My two visits to Boston (Harvard) in the summer and winter of 2009 were heartwarming experiences.

My twin brother Victor Chua and his wife Grace Yong were likewise extremely supportive, particularly in helping me transition back into Singapore. They have always gone that extra mile.

Above all, I would like to thank God for opening the door to Toronto, and for blessing me with such wonderful social networks -- family, friends, colleagues, and professors alike.

Vincent Chua, University of Toronto, August 2010

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Table of Contents

Chapter 1: Analyzing Social Capital in Context ……………………………….……….…...…………... 1

Chapter 2: The Human Capital Society ……………………………………………………..…………... 18

Chapter 3 (Paper 1): Categorical Sources of Varieties of Network Inequalities ……………………………...… 44

Chapter 4 (Paper 2): Social Networks and Labour Market Outcomes in a Meritocracy ...……….………….... 85

Chapter 5 (Paper 3): The Invisible Hand of Social Capital ……………………..……………………………….. 128

Chapter 6: Conclusion …………………………….………………………………………...... 164

Appendices: Name Generator and Questionnaire …………………………………………………….... 175

List of Tables

Chapter 3 (Paper 1)

Table 1: Number of Types of Social Capital by Gender and Ethnicity 58

Table 2: Categorical Inequality in Social Capital 63

Table 3: Education and Inequality in Social Capital 65

Table 4: Work and Inequality in Social Capital 66

Table 5: Household Income and Inequality in Social Capital 67

Table 6: Family Formation and Inequality in Social Capital 68

Table 7: Voluntary Associations and Inequality in Social Capital 70

Table 8: Summary of Interaction Effects 75

Chapter 4 (Paper 2)

Table 1: Descriptive Statistics of Sample of Singapore Citizens and Permanent Residents 100

Table 2: Binary Logistic Regression estimating the Effect of Education on Contact Use 105

Table 3: OLS Regression estimating the Effect of Contact Use on Earnings 108

Table 4: Job Sector Differences in Education, Earnings, Proportion of Job Contact Users 109

Table 5a: OLS Regression estimating the Effect of Contact Use on Earnings by Job Sector 110

Table 5b: OLS Regression estimating the Effect of Contact Use on Earnings by Job Sector 111

Table 6: OLS Regression estimating the Effect of High-Status Job Contact on Earnings by Respondent’s Education 114

Chapter 5 (Paper 3)

Table 1: Sample Characteristics 142

Table 2: Multinomial Logistic Regression estimating the Effects of Accessed (# of University Graduates) and Mobilized Social Capital (Contact Use) on Job Sectors 147

Table 3: Multinomial Logistic Regression estimating the Effects of Accessed (# of Private Housing Dwellers) and Mobilized Social Capital (Contact Use) on Job Sectors 149

Table 4: Multinomial Logistic Regression estimating the Effects of Accessed (# of Chinese) and Mobilized Social Capital (Contact Use) on Job Sectors 150

Table 5: OLS Regression estimating the Effects of Accessed (# of University Graduates) and Mobilized Social Capital (Contact Use) on Earnings 152

Table 6: OLS Regression estimating the Effects of Accessed (# of Private Housing Dwellers) and Mobilized Social Capital (Contact Use) on Earnings 153

Table 7: OLS Regression estimating the Effects of Accessed (# of Chinese) and Mobilized Social Capital (Contact Use) on Earnings 154

List of Figures

Chapter 4 (Paper 2)

Figure 1: Rate of Job Contact Use by Industry 112

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List of Appendices

Appendix A: Name Generator 175

Appendix B: Project Network Questionnaire 176

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Chapter 1 Analyzing Social Capital in Context

Social capital in context

Social capital scholars tell us that job success entails much more than formal skills, training and credentials. They show that even as formal qualifications are important, interpersonal networks are absolutely pivotal for job success (Burt, 1992; Lai, Lin and Leung, 1998; Erickson, 2001; Lin, 2001).

I take an even broader view. Social networks are interpersonal relations which have their more fundamental basis in macro-level structures such as state, economy, education, labour markets and culture. It is these macro-level structures that affect the distribution, role and value of social capital, and subsequently individuals’ job success (Hsung, Lin and Breiger, 2009).

This dissertation is presented in the form of three publishable papers, aimed at advancing our understanding concerning how aspects of social organization affect individuals’ access to and payoffs from social capital in the context of contemporary Singapore. These papers are united by the sociological axiom that while individuals have free-will, they are also constrained by structural forces which affect their experiences with social capital. Indeed, people are not just social networkers manipulating networks for some future advantage. They are networkers operating within realms of social structure: politics and economy, state ideology, bureaucratic administration and other relevant structures of power (Granovetter, 2002).

These stand-alone but interconnected papers may be thought of as addressing two broad research questions. The first concerns the sources of network inequalities: How is social capital distributed among individuals/social groups and why? The second concerns the consequences of network inequalities: What is the impact of network inequalities on job success in different kinds of labour markets? While I have focused 1

on the Singapore context, these questions are more broadly relevant for advancing our understanding concerning how organizations and other institutional arrangements affect the distribution, role and value of social capital in contemporary societies other than Singapore.

Need to examine institutional contexts

Formal skills and credentials constitute critical explanations for how and why some individuals are more successful than others in labour markets (Becker, 1964; Blau and Duncan, 1967; Schofer and Meyer, 2005). And yet, a singular focus on human capital implies a utopian world of meritocracy, whereby educational ‘effort’ and ‘ability’ are the only key ingredients in the social mobility process (Young, 1958). From the viewpoint of a strictly human capital model, social mobility depends mainly on an individual’s ability and determination to make good in an implied Hobbesian struggle for skills and credentials (Baptiste, 2001). But are things that simple?

The theoretical value-added aspect of social capital research is the opportunity it provides for considering the role and impact of interpersonal structures on status attainment. Here, the focus moves beyond economic actors’ accumulation of skills and qualifications, and evokes the interpersonal environments within which economic actors engage one another (Granovetter, 1985; Burt, 1992). Social networks are often a “final arbiter” of competitive success, after human capital elements have all been considered (Burt, 1992:67). Vouching or putting in a good word for someone is an important way of matching seekers to jobs, because it provides more nuanced information than credentials (Granovetter, 1974; Burt, 1992; Bian, 1997). That social capital so often precipitates educational success (Coleman, 1988), matches people to jobs (Granovetter, 1974) and enhances status attainment (Lin, 2001), makes it an extremely important contextual element in social stratification research.

But this begs the question: is analyzing networks on their own sufficient for understanding the full nature of economic action? While social capital is an important structural concept, it does not, by itself, increase our understanding concerning the interrelationship between social capital and the larger institutional environments within which social capital is embedded. We need certainly to expand our knowledge concerning the interplay between social capital and social institutions, organizations, and social history, and not settle for ‘structure’ taking the form of network nodes and edges only (Granovetter, 2002).

Social capital and the problem of individualism

Generally defined, social capital refers to the resources that people have potential access to from being connected to others possessing those resources (Lin, 2001). Social capital is not just a social “relation” binding individuals together, but more strategically, it is a social “resource” that can be mobilized for some expressive and/or instrumental purpose (Lin, 2001). The focal individual (or central node) is here assumed to be an autonomous manager of his/her own personal network: he/she is a network strategist who “invests” in social capital and mobilizes them with an eye to future rewards (Lin, 2001; Wellman, 2007).

Such an autonomous approach may be too instrumentalist however -- as it fails to consider two further aspects of social organization. First, people are not always at liberty to choose their network members: kinship networks are an example of the often ascriptive nature of human relations (Fischer, 1982). Beyond family, social relations often arise from social contexts, rather than from a person’s free-will alone (Feld, 1981). Therefore, it is appropriate to think of individuals not only as managers of their own personal networks, but also as individuals who are tied to networks in less strategic, conscious or intentional ways (Lin and Ao, 2008; Small, 2009).

Second, an instrumentalist viewpoint falls short of addressing the question of how social capital may integrate with larger aspects of social organization. Using the example of Burt’s theory of structural holes (1992), Granovetter (2002) argues that while strategists may often manipulate networks for personal gain, that is, by positioning themselves between unique clusters of information (and preventing others from filling the gaps), focusing on network structures alone often obscures the nature of the relationship between social institutions and the networks themselves.

On this point, Feenstra and Hamilton (2006:22-23) have paraphrased Granovetter well:

Granovetter has warned repeatedly that simply evoking network structure (that is, centrality or structural holes) is causally insufficient without a more developed sociological understanding of the historical context... Instead, he argues that network analysis should be less formal and methodological and more linked to standard sociological concerns with power, social structure and institutions than is now the case... In calling for a sociological understanding of context, he wants to move an embeddedness perspective away from the structural arrangement of networks to institutional foundations of economic action.

The intended contribution of this dissertation is therefore to specify in a systematic manner, the “institutional foundations” that surround structures of network ties. More directly, the intended aim is to demonstrate how macro-level factors such as 1) state rule and their attendant systems of categorical administration and domination, 2) specific aspects of political economy such as the nature of the link between education and labour market systems, and 3) the persistence of class, gender and race as social divisions (rather than merely innate attributes), produce consequences such as 1) the unequal distribution of social capital between gender and ethnic groups, and 2) the unequal role and payoffs to social capital for different kinds of individuals in different kinds of labour markets.

Culture as institutional rather than internal

Whereas culture is often interpreted as representing values or preferences, culture is in fact, very much structural in nature. According to Swidler’s (1986) “toolkit” metaphor, culture is not so much a “strategy in the conventional sense of a plan consciously devised to attain a goal”, but rather, “a general way of organizing action” (Swidler, 1986:277). Indeed, “people do not build lines of action from scratch, choosing actions one at a time as efficient means to given ends... instead, they construct chains of action beginning with at least some pre-fabricated links... culture influences action through the shape and organization of those links, not by determining the ends to which they are put” (Swidler, 1986:277).

Culture is routinized and institutionalized in everyday life. It is, as White (2002:131) puts it: ...a process of actors “finding footing in interactions with other actors who are also seeking footings in what thereby becomes a sustained course of action”. The persistence of pathways and sustained lines of action working through culture is an important aspect of the reproduction of inequalities in everyday life and needs to be considered alongside more obviously institutional mechanisms.

As far as culture is treated as a set of values or preferences, this dissertation adopts a clearly anti-culturalist stance, but to the degree that culture is not just about intentional preferences but unconscious “strategies, styles and habits” (Swidler, 1986:277), then culture has an institutional side to it, and should be incorporated in the analysis of economic life, social capital and social stratification (Hamilton and Biggart, 1988).

The point is not to claim that culture is “everywhere”, or even to say that everything is eventually reducible to culture (Zelizer, 2002:109). Rather, we need, more carefully, to underscore that culture is a set of beliefs, shared understandings and practices that often reflect constraints which clearly have an institutional basis. For example, the prevalence of social networking among Chinese economic actors (in the form of

‘guanxi’), may not be due primarily to the fact that Chinese value or prefer social networking more than any other ethnic group, but more structurally, because Chinese have for a long time now, been concentrated in private sector jobs within the Chinese diaspora, and these jobs require the active mobilization of networks (Xin and Pearce, 1996). On the surface, social networking may often be misrecognized as a purely cultural form, when in fact institutional factors undergird those cultural forms (Bian, 1997).

Social capital in the context of Singapore

The societal context being analyzed is contemporary Singapore. All three papers utilize representative data from the 2005 Project Network Survey , which contains detailed information about the personal networks of a representative set of Singapore citizens and permanent residents aged between 25 and 55. The original sample size is 1043 (but the valid sample sizes will vary according to the paper). Each paper has its own data and methods section so I will not go into the details of source and methodology at this juncture. The data was collected with the help of a professional survey research company, AC Nielsen, based on a research grant (R-111-000-051-112) from the National University of Singapore (NUS).

Singapore serves as an excellent fieldsite for exploring the role and impact of institutional factors on social capital, for various reasons. First, Singapore is a racially- stratified society. That is, despite the ethnically-heterogeneous composition of Singapore, the powerful state deals with its people in terms of racial categories: Chinese, Malay, Indian, Others or ‘CMIO’ for short. ‘CMIO’ is a deliberate highlighting of racial divisions by a highly technocratic, managerial and administrative state (Clammer, 1998). Beyond innate attributes, ‘CMIO’ is a racial principle with real consequences for people’s life chances (Hechter, 1978; Rahim, 1998). The question of how racial principles operate in everyday life and of how they subsequently affect the distribution of social capital, is an important one that this dissertation aims to address.

Second, Singapore, despite its modernity, remains a rather strong patriarchal society (Chan, 2000). This patriarchy is seen most clearly in the work-family interface, where gender-segregated roles prevail, mainly in the form of women still playing a much more active role in the home despite their simultaneously active engagement in paid work (Straughan, 1997). Ironically, while Singapore women have outpaced men in their educational attainment, women are still much more likely to remain at home because of family and childcare. Hence, like race, gender is an important organizing principle which we can expect, will significantly impact the distribution of social capital.

Third, Singapore is a decidedly meritocratic island city-state, where formal credentials are highly emphasized at every stage of a student’s and worker’s life (MacDougall and Chew, 1976; Evans and Rauch, 1999). The strong emphasis on human capital in many Singapore labour markets makes it an excellent context within which to explore the interrelationship between meritocratic constraints and social capital. We can ask for example: to what extent do credentials and other kinds of meritocratic requirements suppress the role and value of social capital in job matching and remuneration? Can human capital and social capital be simultaneously important even in highly- meritocratic labour markets? If yes how?

My theoretical opportunity resides in the fact that while Singapore is a broadly meritocratic society, there are substantial variations in the extent to which this meritocracy is enforced in the various labour markets. The state sector, comprising the civil service, statutory boards and government-linked companies (GLCs), is clearly the most meritocratic of the job sectors, followed by the multinational companies (MNCs), and the small business sector (SMEs). While the powerful state sector exerts significant pressure on the other sectors to adopt similarly meritocratic practices (DiMaggio and Powell, 1983), this pressure is by no means totalizing. Variations in levels of meritocracy across different types of job sectors afford an opportunity to measure how

8 meritocratic constraints affect the role and value of social capital in different kinds of labour markets.

The following sections provide a brief summary of the contents of each paper. Many of the details are in the papers themselves, so my summaries will not pretend to be exhaustive. My aim is more general: to sketch the broad arguments and highlight some of the role and impact of macro-level factors on the distribution, role and value of social capital in Singapore, and thereby contribute to broader concerns about how social capital operates in institutional contexts that are racialized, patriarchal, and meritocratic.

Categorical sources of varieties of network inequalities

The first paper examines the categorical sources of several forms of social capital. While research indicates that social capital tends to be unequally distributed along gender and ethnic lines (e.g. see Lin’s 2000 review), what remains less clear is how gender and ethnicity: as organizing principles rather than as individual innate attributes (Omi and Winant, 1994; West and Fenstermaker, 1995; Tilly, 1998), affect the distribution of social capital in everyday life.

There is another issue. Examining the literature on social capital, it is not hard to notice that gender inequalities in social capital tend to be discussed in terms of men’s and women’s unequal access to forms of social capital such as non-kin (Moore, 1990), weak ties (McPherson and Smith-Lovin, 1982) and men (Erickson, 2004), while ethnic inequalities in social capital tend to be discussed in terms of ethnic groups’ unequal access to social capital such as occupations (e.g. doctor, lawyer, teacher) (Moren-Cross and Lin, 2008), the well-educated (Wilson, 1987) and dominant ethnic groups (Moren- Cross and Lin, 2008). And yet this – the fact that gender and ethnicity often produce characteristic forms of social capital is seldom pointed out, problematized or further theorized.

My data highlights that powerful gender and ethnic groups are not only more likely to have more social capital, they also tend to control distinctive bundles of social capital respectively. For example, I find that whereas Chinese (relative to Malays and Indians) tend to have greater access to well-educated, wealthy and Chinese social capital (but not non-kin), men (relative to women) tend to have greater access to men, non-kin and weak ties (but not well-educated, wealthy and Chinese social capital). How can we explain these distinctive patterns of network inequalities?

As social capital often arises from organizational settings (Feld, 1981), one way of addressing the above question is to ask how gender and ethnic groups are distributed in settings that matter for social capital formation. The way that gender and ethnic groups are distributed in places such as schools, paid work and voluntary associations will provide important clues as to the kinds of contextual mechanisms driving gender and ethnic inequalities in social capital.

My analysis shows that ethnic groups’ unequal access to high education (but equal access to paid work) and gender groups’ unequal access to paid work and voluntary associations (but equal access to high education) account for much of why gender and ethnic groups tend to access distinctive forms of social capital.

Institutions tend to add social capital equally to individuals, regardless of their gender or ethnicity, suggesting a persisting logic of meritocracy governing how institutions add social capital to members. The problem of network inequality in Singapore is therefore not so much the issue of unequal increments in social capital (arising from organizations), but more primarily, the issue of unequal entry into those organizations. The paper delves into some socio-historical details concerning how specific organizational gatekeepers have disadvantaged less powerful gender and ethnic categories/groups.

Meritocratic constraints and the role and value of job contacts

From sources of social capital, I move on to examining the consequences of social capital. In the second paper, I ask: what is the role and impact of job contacts on status attainment (i.e. monthly earnings) in labour markets varying by levels of meritocracy? While studies have established the generally useful and leveraging role of job contacts (e.g. Granovetter, 1995 [1974]; Bian, 1994; Coverdill, 1998; Fernandez, Castilla and Moore, 2000), can we expect job contacts to work the same way in all kinds of labour markets? This seems a logical question, but the relative role and usefulness of job contacts within and between labour market contexts remain relatively unexplored in the literature. This paper will demonstrate that the role and payoffs to job contacts are often not uniform, but contingent upon the characteristics of labour markets: for example, I show that in labour markets that emphasize meritocracy, job contacts tend to be less useful and leveraging.

Using previous research drawn from the United States as a reference point, but comparing it with Singapore data, I ask: why is the use of job contacts is more prevalent in America than Singapore? Rather than rely on cultural explanations, I argue that contextual factors such as national variations in the relationship between education and labour market systems in both countries are important determinants of contact use (Hall and Soskice, 2001; Allmendinger, 1989).

I distinguish between two concepts in the varieties of capitalism literature: ‘liberal market economies’ (LMEs) and ‘coordinated market economies’ (CMEs). In LMEs, of which the United States is an exemplar, the supply and demand sides of the labour market are ‘loosely-coupled’, that is, education systems send only weak signals to employers about prospective workers. In CMEs by contrast (e.g. Singapore), the supply and demand sides of the labour market are ‘tightly-coupled’, meaning that education systems send strong signals to employers about prospective workers.

My general argument is: the more loosely-coupled the education and labour market systems, the more job contacts are needed to fill informational gaps in job matching.

The more tightly-coupled the education and labour market systems, the less job contacts can influence the job allocation and remuneration process as formal qualifications are overwhelmingly important. My data demonstrates that in CME environments such as the state bureaucracy, job contacts bring no distinct advantages as appointments are made exclusively on the basis of the academic credentials of the candidates. In LME environments, on the other hand, job contacts are more useful among less qualified job searchers in the private sector (which is an LME environment).

The Chinese are especially likely to use job contacts, not so much because they are ‘Chinese’ (i.e. culturally idiosyncratic), but more structurally, because of their historical role in the small business sector. Today, Chinese in Singapore continue to hoard private sector jobs, and they do so by evoking job contacts.

In the state sector, credentialing requirements tend to suppress the role and value of job contacts. Well-educated job-seekers are significantly less likely than less well-educated job-seekers to rely on job contacts. Those seeking entry into formal industries, such as education, health and social work, are much less likely to rely on job contacts than those seeking entry into less formal industries such as retail, wholesale and construction.

Beyond job contacts: Meritocratic constraints and the more subtle importance of social capital

If job contacts are often ineffective in meritocratic labour markets as the second paper suggests, then the third paper asks: does it mean therefore that social capital is consigned to play a marginal role in meritocratic recruitment and remuneration? The answer is a definitive ‘No’: social capital continues to be important even in labour markets that emphasize meritocracy, but in ways other than the active mobilization of job contacts.

By distinguishing between accessed social capital and mobilized social capital (as in Lin, 2001), the third paper argues that whereas job contacts (i.e. mobilized social capital) may often be ineffective in meritocratic labour markets, broader forms of social capital

12 other than job contacts (i.e. accessed social capital) remain extremely useful and leveraging.

The distinction between accessed and mobilized social capital is an important one because job contacts represent only a subset of the total capacity of a person’s network, and are therefore an inadequate representation of the total potential of his/her social resources (Lai, Lin and Leung, 1998; Lin and Ao, 2008). By examining the role and value of accessed and mobilized social capital in tandem , this paper contributes to research concerning the role of intentional and less intentional modes of network utilization and their associated payoffs in labour markets. In view of the embedded nature of accessed social capital (here contrasted with mobilized social capital), I have used the terms ‘invisible hand’ and ‘visible hand’ of social capital to designate them respectively (as Lin and Ao, 2008 had also done).

Much of the material benefits that people experience in meritocratic societies are really the result of more incidental and unconscious pathways of networking: the gains that people get from social capital are not always due to the networks they activate , but the networks they have . While education may be extremely important in a meritocracy, social capital in the form of the invisible hand is shown in this essay to be critical for job success.

Strong accessed social capital effects suggest that status attainment in a meritocracy is never about educational performance alone, but access to social capital as well. The allocation of rewards in meritocracies is not just about effort and ability, but about categorical processes such as race, gender and access to segregated networks. In practice, inheritances, cultural capital and human capital are often channelled from person-to-person, situation-to-situation through networks -- institutions and bureaucratic structures notwithstanding.

Strengthening contextual foundations

Taken together, this dissertation, whether discussing sources or consequences of social capital, seeks conscientiously for explanations at the level of structure and institutions. The broad strategy is, as C. Wright Mills recommends in the Sociological Imagination (1959): to let the macro explain the micro. The macro elements are the political economy, social administration and power structures constituting Singapore society. The micro elements are the biographical elements, namely Singaporeans’ experiences with social capital and job success.

In adopting an institutionally-focused perspective, this dissertation elucidates the inextricable link between the “public issues” of powerful social structures and the “private troubles” of social capital management (Mills, 1959:8). As Granovetter (2002) recently notes, there is a real need to link network analysis to standard sociological concerns with power, social structure and institutions.

The next chapter will provide, appropriately, a brief introduction and account of the Singapore context. The background information provided will help situate our study of social capital in a broader contextual, institutional and socio-historical framework.

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Chapter 2 The Human Capital Society

Charlie Rose: You seem to be sensitive to the issue of what’s called nepotism. Lee Hsien Loong: We are very sensitive. Charlie Rose: Tell me about this sensitivity. Lee Hsien Loong: The whole of our system is founded on a basic concept of meritocracy. You are where you are because you are the best man for the job, and not because of your connections or your parents or your relatives... Charlie Rose: So if some journalist writes about nepotism and you think it’s not true... Lee Hsien Loong: Well, then we sue him, as we did recently. Straits Times, 16 April 2010

Singapore is an intransigently meritocratic state. If as Hobsbawm and Ranger (1983) note: nations are built upon “invented traditions”, then for the Singaporean nation, the tradition of meritocracy is one well-versed mantra: “you are where you are because you are the best man for the job and not because of your connections...”

The enshrining of ‘best man’ policies in Singapore, particularly in education and employment has created a palpably human capital society, whereby cohorts of students have for decades now, competed aggressively for the best schools, grades, scholarships and jobs (Gopinathan, 1996; Tan, forthcoming). A culture of academic examinations buttressed by a rigorous private tuition regime has become so entrenched among students that the Ministry of Education has more recently sought to shift the curriculum away from rote learning and introduce the teaching of soft/creative skills alongside a continued emphasis on technical subjects (Straits Times, 9 March 2010).

A recent survey conducted in 2004 indicated that Singaporeans are most likely to deem education as being most important for social mobility, followed by hard work, ability, social connections and luck (Tan, 2004). The fact that social connections was ranked fourth (only after education, hard work and ability) implies the great extent to which meritocratic values have become widespread in Singapore. And yet more than a set of values, meritocracy has become institutionalized. For generations now, Singaporeans 18

have imbibed the message that educational achievements are alone sufficient for job success. The result is a school system that cultivates a love for academic grades rather than a love for learning (Dore, 1976). It has been argued that university graduates in Singapore may be over-educated but under-skilled (Appold, 2005).

Meritocracy as a social system with contradictions

Meritocracy is a social system that allocates rewards to individuals based on the principle of educational merit (Goldthorpe and Jackson, 2008). As noted by Michael Young (1958), merit is the combination of “ability” and “effort”. The ideological appeal of meritocracy lies in its -- at first glance -- impeachable logic: people are rewarded based on some measure of how naturally gifted they are and how much effort they have been willing to put in. Success is individualized, and if failure occurs, the fault is implied to be wholly personal as well.

Indeed, the individualism implied in meritocracy leaves no conceptual space for some rather pertinent questions: can we rightly assume that ability is entirely biological, and unaffected by social factors? Do class resources such as family background, private tutors and personal networks compensate for personal lack in ability and effort? Do unit increases in ability and effort pay off equally well for different groups of people?

A meritocracy is most fair and impartial when starting lines are approximately equal (e.g. everyone is poor or rich). However, when applied to advanced societies, meritocracy becomes but a fortuitous agent for elitism and social reproduction. Meritocracies have an important hand in alleviating family background inequalities, but they do not by any means, eliminate it. For one, children from wealthier backgrounds inadvertently get a head start in life as they get to go to better schools (Gillis, 2005).

Pre-existing class divisions combined with a highly-meritocratic education system have enabled wealthy families to consolidate durable bases of material and symbolic power

20 in Singapore (Tremewan, 1994). While almost all Singaporean children have basic access to elementary school, wealthier children are exposed to better resources and thus stand a better chance of doing well at school (Barr, 2006). Examinations are meritocratic (and in this regard, many less fortunate children have done admirably well), but family resources spread a safety net for the less academically inclined children of wealthy families (see Lareau, 2000).

Because class factors are so important to academic achievement, homogeneously poor groups such as ethnic minority Malays in Singapore are particularly disadvantaged. While there are many Chinese and Indians who are not wealthy, the Malay community stands apart as a group that is almost uniformly disadvantaged (Li, 1989; Rahim, 1998). Like blacks in the United States (Wilson, 1987; Omi and Winant, 1994), Malays in Singapore are more likely than the other ethnic groups to have to contend with poverty and stigmatizing attributes such as ‘poor’ and ‘lazy’ (Hirschman, 1986; Rahim, 1998). In the discourse of meritocracy, ethnic minorities’ poorer performance in school is often attributed to factors such as lack of motivation rather than more accurately their lack of class resources (Rahim, 1998).

While women are less likely to experience the kinds of family background disadvantages that Malays do, they are disadvantaged in other ways. For example, although gender inequalities have narrowed substantially in education (Chang, 1995), Singaporean women continue to be significantly disadvantaged at work and at home. Many well-educated women are engaged in paid labour markets, but the PMT (professional, managerial and technical) ranks are still dominated by men (Chan, 2000). At home, many working women are expected to shoulder the bulk of childcare, despite their already stressful work lives. Meanwhile, males, particularly traditional males, remain generally reluctant to contribute more actively to domestic tasks. When childcare becomes urgent, it is usually the woman who leaves the workplace (sometimes temporarily) rather than the breadwinner male (Straughan, 1997).

Meritocratic societies are unequal societies. A meritocratic society will not guarantee an absence of gender or racial biases. In fact, as meritocracies cannot eliminate family background inequalities (for example, by abolishing inheritances and other intergenerational transfers), ethnic boundaries operating through class mechanisms continue to be salient (Hechter, 1978). Meritocracies do not eliminate patriarchy either. Indeed, the gender script (that work is the place of men and home is the place of women) remains a durable force in contemporary societies. While meritocratic norms may be expected to eventually remove gender biases in a distant future (Blau and Kahn, 2006), notions of patriarchy still cling on, if not in the minds of individuals, then in the practices of institutions (England, 1994; Tilly, 1998).

In Singapore, Confucianism and patriarchal themes such as choosing the ‘best man for the job’ continue to enforce gendered, racialized (namely Chinese) and class-based (elite versus not) notions of society, even as meritocracy is being emphasized. In the rest of this essay, I discuss various aspects of the reproduction of class, racial and gender relations by describing relevant aspects of Singapore’s historical, political and socio- economic development.

Educating labour for foreign capital in a merit-based survivalist environment

The eviction of Singapore from Malaysia in August 1965 (due primarily to Singapore’s insistent stand on meritocracy and its subsequent refusal to accede to Malaysia’s Malay- first or ‘Bumiputra’ policy), provided occasion for the ruling People’s Action Party (PAP) to play on public insecurities and propagate an ideology of survivalism (Chan, 1971; Tremewan, 1994). This rhetoric of survivalism was based on the sudden and anguishing fact that Singapore was now independent from Malaya with no hinterland to build a viable economy from (Lau, 1998).

It was in the context of such emergency conditions that the ruling PAP legitimated their right to rule with an indomitable iron fist (Tremewan, 1994). On the premise that a

22 materially-deprived economy demanded close and urgent attention, Singaporeans were exhorted to work hard and not be side-tracked by political concerns (Chua, 1995). The lack of natural resources in the island city-state, coupled with its geographical realities (particularly its small size), have enabled the Singapore state to generate a discourse underscoring the redemptive role of an important substitute --- human capital.

Unlike the other East Asian economies (e.g. Japan, South Korea and Taiwan) which built their post World War II economies on the strength of entrepreneurial ventures initiated by local capitalists (hence the rise of economic giants such as Toyota, Honda and Samsung), Singapore had chosen (rightly or wrongly) the path of MNC-led growth (Schuman, 2009). To stem the tide of growing unemployment, Singapore was promoted by its state elites as a low-cost manufacturing base for foreign capital (Castells, 1988). It so happened that during the 1960s and 1970s, American and European companies were looking for offshore manufacturing bases for their electronics sector, and Singapore was fortunate enough to have had, at that time, an attractive mix of developed infrastructure, tax incentives, and educated labour (Tremewan, 1994).

While Lee Kuan Yew and the Economic Development Board (EDB) have often been accredited for bringing Singapore from “Third World to First World” (Lee, 2000), fortuitous events and circumstances in the 1960s and 1970s such as the outsourcing of manufacturing jobs by American and European corporations (such as Texas Instruments, Hewlett Packard and Philips), along with the much slower rate of development in the rest of Southeast Asia, and most significantly, the closed-door- policy of China, afforded Singapore a thirty year window of opportunity to grow its economy. Without this window, Singapore would not have survived.

Today, multi-national companies (MNCs) continue to be an important part of Singapore’s economic landscape, but competition has certainly intensified as MNCs constantly seek out cheaper locations (Ngiam, 2006). To remain competitive, Singapore has had to re-invent itself, that is, to upgrade its human capital and technological base

23 while keeping wages in high-end industries relatively low. The latest direct foreign investments (FDIs) have been in the areas of pharmaceuticals, biotechnology and intellectual property (Pereira, 2008).

Although Singapore will never again be competitive in low-cost manufacturing because of China’s expansion, its competitive advantages lie in mid-level production and servicing the Asian-Pacific region on behalf of foreign capital (Tremewan, 1994). In the same way that the Chinese merchants of old mediated transactions between locals and Europeans during the colonial era, modern Singapore continues to play a brokering role on behalf of foreign capital. In network terms, Singapore fills a “structural hole” between East and West (Burt, 1992). The fundamental role of Singapore has, for a long time, been the provision of affordable but good quality products and services for foreign capital in order that, on the domestic front, Singaporeans may keep their jobs and experience social mobility. The implicit contract between ruler and ruled in Singapore (or more aptly ‘Singapore Inc.’) is: grow the economy, and we will vote you in (Ho, 2006).

Manuel Castells has called Singapore the “quintessential developmental state” and for good reason (Castells, 1988:4). A developmental state is an economic system where economic growth is assigned top priority and used to legitimate political rule. It is a state which selects political leaders based on a rigorous system of academic evaluations (Loriaux, 1999). Even though most developmental states operate on open and free- market principles, political elites are de facto chairpersons in what are essentially state enterprises. In a developmental state, the rulers are entrusted with the mandate of growing the economy on behalf of the ruled. The ruled are in turn willing to exchange political rights for economic growth (Woo-Cummings, 1999; Ho, 2006).

Educating the masses in order to elicit the best for the state sector

Education is a critical mechanism through which the powerful state identifies, selects and grooms its future elites and leaders (Barr, 2006). Singapore is like a Confucian Mandarinate. The winners of the rigorous education race are appointed as important officials such as “mandarins” in the state sector (see Weber, 1983). In a Mandarinate system, intellectual achievement is seen not only as a mark of mental acuity, but also a reflection of character, strength of purpose, dedication, and moral virtue (Straits Times, 10 November 2006). In Confucianism, the state is more than a bureaucratic apparatus. It is a moral authority that governs the people in a paternalistic manner (Chua, 1995).

In Singapore, examination stalwarts are brought into elite government with state- sponsored scholarships to prestigious universities abroad in exchange for some years of bonded service. While the scholarship system has paved the way for many bright but less well-off students (Barr, 2006), recent evidence points to the fact that an increasing number of scholars are from upper-middle class backgrounds, and that educational resources are skewed in the direction of elite families (Barr and Skrbis, 2008).

The scholarship system has created a situation whereby talent concentrates in the state sector, leaving the MNCs and small business sector with less talented individuals (Chan and Ng, 2000). As the state hoards the national talent, the other labour markets have had to settle for an academically less talented pool (Ngiam, 2006). The state’s justification is that without a competent public sector, the rest of society would crumble (Lee, 2000). Although examination-based hiring may not (in retrospect) always select the best people (afterall, academic ability is only one aspect of ability), the signalling role of educational credentials remains highly treasured in the state sector.

Mandarins in the small but very powerful state sector

The state sector, which comprises 1) the civil service, 2) statutory boards and 3) government-linked companies (GLCs), is a highly formal social system (Quah, 1998; Neo and Chen, 2007). Arguably, the state sector ceases to be meritocratic when job

25 rewards are allocated based on past performance, but a meritocratic system gains its legitimacy by rewarding educational tangibles (Collins, 1979).

While the meritocracy in Singapore was the brainchild of Lee Kuan Yew, its implementation in the context of the civil service was (particularly in the early days) entrusted to his very able Finance Minister, Dr Goh Keng Swee. Being a PhD holder in Economics from the London School of Economics (LSE), Goh Keng Swee “placed a high premium on intellectual ability and academic brilliance, rather than experience … and as Goh had carte blanche to hire anyone from the list of government scholars given to him, he paved the careers of many young officers” (Neo and Chen, 2007:163).

Singapore’s educational tracking system extends into the military service that all 18 year old Singaporean men undergo. Typically, those with the most excellent GCE ‘A’ level grades are assigned to scholar or “white-horse” platoons where they do officer cadet training (OCS) and are considered for prestigious government scholarships to Ivy- League type universities abroad (Barr, 2006). After their three to four year stints abroad, these officer-cadets return to Singapore to serve their bond for their state sector employer (Barr, 2006). The scholar can break the bond if he/she wishes, but is morally obligated to fulfill it.

Some of these scholars are assigned to government-linked companies (GLCs) upon graduation. As GLCs are state enterprises run on a commercial logic, the prevailing personnel policy is, as in the civil service, to “recruit in the open market, both at home and abroad on competitive terms” (Krause, 1989). GLCs often have access to the civil service’s pool of talented human resources. Indeed, some high-ranking civil servants sit on the boards of GLCs and several are seconded to them full time (Krause, 1989:443).

Although run on free-market principles, GLCs have the support of state capitalization. One Singapore study found that although GLCs “are no more or less liquidity- constrained in their investment decisions than their private sector counterparts”, they

26 are nevertheless, “rewarded in financial markets with a premium of more than 20 percent” (RamÃrez and Tan, 2003:20). The authors posit that this has to do with the market’s perception of government companies being extremely reliable. The good economic performance of GLCs ensures dividends for investors and good salaries for workers. As salaries in state sector jobs are about 10 percent higher than wages in comparable private sector jobs (Evans, 1995), many graduates from the local universities and polytechnics have striven to enter the state sector (MacDougall and Chew, 1976:309; Neo and Chen, 2007).

Merchants in the large but relatively powerless small business sector (or ‘SME’ sector)

Along with the MNCs, the private sector comprises some 126,000 small and medium sized business enterprises (SMEs). Many of these businesses are in industries such as finance, retail and wholesale, construction and light manufacturing (Chan and Ng, 2000). While SMEs value good education, they do not enforce it to the same exacting degree as the state sector. The SME sector is on some level less formal than the state sector, that is, job contacts are important channels of job matching, even as credentials are valuable. The SME sector is dominated by Chinese employers and workers who rely heavily on networks (‘guanxi’) to recruit and get their work done. Anecdotally, in Singapore’s high-end banking sector, recruitment is based on ‘old boy’ networks. Here, job candidates from prestigious predominantly Chinese and mission schools are especially advantaged.

The small business and financial sectors have their origins in the colonial era. During that time, Singapore was used by the British as a trading post for goods flowing between the continents. Its strategic location and naturally deep harbour made Singapore a good stop-over location for ships travelling between eastern and western trade routes. The British brought their merchandise to the region (e.g. tea and spices from India), and sold them to the natives through Chinese merchants who had intimate knowledge of the local markets. Chinese labourers came to Singapore via a patronage

27 system called credit-ticket, whereby wealthy Chinese merchants paid for the tickets of Chinese immigrants in exchange for some future labour and subservience (Visscher, 2007).

Before 1867, the British did not play an active role in the day-to-day running of Singapore, but ruled from their administrative base in Calcutta. They wielded administrative control from afar through a system known as Kapitan, which is a decentralized system of control that appoints local headmen over each racial group. Given their strong links with clan associations and secret societies, the rich Chinese merchants were rulers over the Chinese community.

Arguably, the use of networks within the private sector started with the secret societies and clan associations. Trade networks between the Malayan interior and the port cities (Singapore and Penang), and migration networks between China and the port cities were organized along regional, dialectical and clan lines, partly because of ethnic occupational specialization, but most times because of secret society territorial and labour control. The history of Singapore/Malaysia is really the history of Chinese secret societies versus foreign/colonial capital. On one hand, Chinese middlemen and labourers hoarded work opportunities in the trading, retail and construction sectors. On the other hand, foreign capital exploited cheap labour to boost their entrepreneurial ventures.

Some secret societies engaged in criminal activity. The colonial authorities had tried to decimate them and they succeeded to some extent, but ‘guanxi’ as a culture survived well in the form of the legitimate secret societies: the clan associations! In fact, between the 1960s and 1980s, there arose, with the help of a group of Chinese-educated elites, a state-supported institutional revival of ‘guanxi’ which saw the increased role of Chinese clan associations within the small business sector (Visscher, 2007).

State sector and small business sector as two very different cultural worlds

From the early days of British rule, a number of Straits Chinese (i.e. Chinese with Malay ancestry) and Indian immigrants were co-opted by their colonial masters into the civil service. Having been educated in English schools and having a relatively strong command of the English language, these immigrants were of valuable use to the British.

At the same time, large groups of Chinese immigrants had already settled in Singapore (from the conflict-ridden mainland) and were eking out a living. These were coolies and labourers, who spoke a variety of Chinese dialects and had no knowledge of the English language, but who were desperate for work in order that they may support their families back home. The bulk of colonial attention went towards ensuring superior rights and privileges for the landed Malay aristocracy, Straits Chinese merchants, and a small group of elite Indian administrators, but relatively little attention was paid to poorer Chinese (indentured) labour (Visscher, 2007) or Indian plantation workers (Jain, 1970). These workers were supervised by co-ethnics of higher status, who acted as middlemen and assistants for the Europeans.

Interestingly, the cultural divide between English and ethnic (or more specifically, Chinese) would continue to persist in post-colonial and contemporary Singapore. Lee Kuan Yew (otherwise known by close friends as Harry) was himself a Straits-born Chinese educated in premier English schools such as Cambridge and the London School of Economics (LSE). Along with a mostly English-educated group of nationalists and some Chinese-speaking pro-communists, Lee Kuan Yew’s People’s Action Party (PAP) wrestled control from the Labour Front movement and won the 1959 General elections on the back of huge support from the Chinese-educated masses (Bloodworth, 1986).

However, after the elections, ideological tensions began to surface between the English- educated Lee faction and the Chinese-educated communist faction over Chinese sympathies for the Cultural Revolution. This culminated in a party split in 1961, with Chinese-educated PAP members eventually leaving to form a separate party, the

Barisan Socialis (Bloodworth, 1961). Communal politics expressed and framed in terms of ‘English versus Chinese’ were the order of the day (Huang, 2008). While Lee was preparing the nation for merger with Malaya and thus was anxious to downplay the Chinese element, the Chinese-educated badgered for greater institutional recognition of their culture and education (Wong and Apple, 2002).

In 1966, the Barisan Socialis walked out of parliament, thus relinquishing to the PAP total state power. All seats in Parliament were henceforth PAP seats -- until 1981, when J. B. Jeyaratnam won an opposition party seat in the Chinese-educated ward of the Anson constituency. This loss of a single seat devastated the PAP and fostered a gulf between the predominantly English-educated state and a segment of the Chinese- educated population (Jones and Brown, 1994).

As Singapore embarked on its MNC-led industrialization program, English quickly became the key language of public administration, international business and higher education. The Chinese language alongside other mother tongues namely Malay and Tamil were retained but their role was more symbolic than instrumental. The mother tongues were not official working languages but languages to be used and cultivated at home. They were taught in schools as second languages and promoted as a form of Asian tradition to balance the tide and perceived threat of western influence (Goh Report, 1979).

The rise of English was met with some resistance. During the 1991 General Elections (with Goh Chok Tong as Prime Minister), four parliamentary seats were lost to the Chinese-educated opposition. Interestingly, it was not the ostensibly democracy- hungry middle classes that voted against the PAP, but the Chinese-educated working classes (Jones and Brown, 1994). With state resources working in favour of foreign capital and a wealthy English-centered state, the Chinese-educated have increasingly felt alienated and powerless. Although many among the Chinese-speaking have jobs

30 within the SME sector, their salaries pale in comparison with salaries in the much more prestigious state and MNC sectors (Evans, 1995).

The cultural divide between English and Chinese has surfaced again in much more recent times. The state is currently in the process of tweaking its elementary school education system, and one proposed measure has been the assigning of lower weights to the Chinese language (and other mother tongues) while subsequently increasing the weights to English, Mathematics and Science (Straits Times, 4 May 2010).

For several years, a group of English-speaking parents have argued that maintaining equivalent weightings would disadvantage children from English-speaking homes and penalize their performance in the other three subjects, namely English, Mathematics and Science (Straits Times, 4 May 2010). Predictably, several influential Chinese individuals and clan associations spoke out against the proposal. One perceptive writer (to the Straits Times on 8 May 2010) had noted that such a policy would inadvertently disadvantage the less privileged Chinese-educated masses:

This is not just an educational issue. It’s a socio-economic issue. Children from disadvantaged families who may be strong in Mother Tongue will be kept out of the best secondary schools!

Due to pressures from Chinese (and other mother tongue)-educated groups, the state had most recently, decided not to implement the proposed change in weighting, but instead, to change the manner in which mother tongue languages are taught in schools (Straits Times, 12 May 2010).

Malay marginality in an English-focused and elitist education system

The rise of English in the Singapore education system has been particularly disadvantageous for lower-class individuals, most of whom grew up speaking the mother tongue at home (whether Mandarin, Malay or Tamil) (PuruShotam, 1989). As

Malays are over-represented in poor families, they have been disadvantaged by the emphasis on English (Rahim, 1998).

By evoking education as the only in-principle legitimate source of social mobility, political elites have been able to account for Malays’ school and job underachievement in terms of the latter’s supposed lack of motivation rather than more structurally, their disadvantaged family backgrounds or linguistic disadvantages (Rahim, 1998). The same discourse is applied to less academically-inclined Chinese: those that underachieve are assumed to be ill-motivated, rather than have lower access to class resources and/or English cultural capital.

The overlapping of ethnic boundaries with class boundaries in Singapore causes race to be an especially salient social division (Hechter, 1978). In Singapore, ethnicity is an exercise in political administration (Vasil, 1995). Singapore comprises some 42 ethnic groups distinguishable along finer racial and linguistic dimensions, but because ethnic identities are often too cumbersome to be administratively useful, the state relies on racial categories to manage the population (Goldberg, 2002). The result is a multicultural population thus simplified into four administratively convenient racial categories: Chinese, Malay, Indian and Others (or ‘CMIO’ for short) (Benjamin, 1976).

The Malays and Indians are relatively homogeneous groups. Malays in Singapore are united by the Malay language, their common position of disadvantage and most of all, their common faith in Islam. The Indians are also united by language and religion. Many Indians speak English and Tamil, and are often Christians, Hindus or Muslims. The Chinese on the other hand are the biggest, most varied and most fragmented group. They are English speakers, Mandarin speakers, Christians, Buddhists, Taoists, free thinkers, rich, poor, middle class, in all sorts of occupations and speakers of various Chinese dialects besides Mandarin. Such heterogeneity ensures that the Chinese are not as close knit as a group as compared with Malays and Indians, and hence many of their ties to community are weaker ties.

‘CMIO’ is not a purely Singaporean invention, but a product of colonial policy. In Singapore, race is not just a sociological myth to be debunked, but a reality that continues to structure society in tangible ways beyond colonialism (Clammer, 1998). In Singapore, every child is racially-typed at birth. Administratively, the child is assigned the father’s race, with all ethnic ambiguities generated by intermarriage or family history conveniently discarded in favour of a single racial identification (Chua, 2003). For official purposes, these single racial classifications are indicated on the child’s identity card and become a permanent part of his/her ascribed identity for the rest of his/her life.

The ideal Singaporean is upheld as one who successfully blends both Asian and western identities but who privileges the former in his/her identity. Indeed, Singapore’s society and industrialization is a rigid form of rational education which refuses to acknowledge its compellingly western roots (Clammer, 1998). The result is scientifically rational workers who are trained in western technology, but who are at the same time, ethnic (i.e. interpreted Asian). To the state, ethnicity, particularly in the form of rarefied Mandarin, is perceived to be especially important for economic development even as western principles are actively used in the management of work systems. Confucian values are perceived in the eyes of a developmental state to encourage virtues such as diligence, thriftiness and honesty. Like the Protestant Ethic, these virtues are believed to aid capital accumulation (i.e. savings and investing) and generate capitalistic expansion on a larger scale (Ong, 1997). It is ironic that Confucian values should be invoked as a factor for economic growth in contemporary Asia, given that those same Confucian values were invoked by Weber to explain the decline of Asia in ancient times.

On the education front, the developmental state has built several Special Assistance Plan (SAP) schools which deliberately uphold a rarefied and standardized form of the Chinese language and culture. In these schools, English and Mandarin are examined as

33 first languages. These schools have impressive infrastructure and are staffed with competent teachers and administrators. Given the Chinese emphasis in these schools, only a few Malays and Indians attend.

The presence of several highly-influential mission schools in Singapore adds to the salience of racial boundaries. As these mission schools maintain upper-class traditions and have large endowment funds supported by influential ‘old boy’ and ‘old girl’ networks, students attending these schools are exposed to better resources. Moreover, as Christianity is emphasized in these schools, Malays (who are predominantly Muslims) get inadvertently excluded.

In Singapore, primary school students are matched to schools based on an allocation system that is sometimes biased. In a 1972 exercise, for example, students were admitted according to three phases. In order of priority, Phase One gave preference to children who already had siblings in the same school. Phase Two gave priority to students whose parents were either alumni or members of the school board. Phase Three opened the competition to the rest through balloting.

When siblings and children of alumni of mission schools are given priority admission, educational privileges and disadvantages are transmitted across generations along both class and ethnic lines. Disadvantaged Singaporeans have often raised concerns about such priority admissions. In July 1983, one perceptive reader going by the pseudonym “Fair Play” wrote to The Straits Times, with following comment:

I believe this is an unfair way of according priority. It will create a situation whereby generations upon generations will monopolize the elite schools and deny outsiders the chance to register.

The government’s response was rather evasive:

It is useful for a school to maintain close ties with its former students in building up an identity and tradition of its own… thus, priority for registration is given to a child whose parent(s) or elder sibling was a former student of the school.

There was tellingly, no attempt by the state to address the more pertinent issues of class and ethnic stratification.

Unfortunately, class and ethnic inequalities originating in the education system often carry forward into subsequent life domains such as the military, where conscripted soldiers are typically assigned to vocations corresponding with their educational attainment. Enlistees with lower levels of education are often assigned to service vocations such as technicians, drivers or cooks. If they are combat-fit, they may end up as foot soldiers or rifleman within the infantry units. Higher-educated Chinese are over-represented in command positions. Malays usually end up as truck drivers (or get assigned to the Civil Defence Force). Lower-educated Chinese and Indians usually become storemen, foot soldiers or armskote men (looking after and cleaning weapons).

In sum, ethnic minorities in Singapore are disadvantaged in at least two ways. On one hand, ethnic groups are unequally treated because of differences in their initial class standing (hence their subsequently unequal access to education), but on the other hand, the class standing of ethnic minorities is itself evidence of unequal treatment and prejudice based on their ethnicity.

Patriarchal relations as distinct from race /ethnic relations

Although women and ethnic minorities are both disadvantaged in terms of their respective locations in gender and ethnic stratification systems, the kinds of structural hurdles faced by women are not necessarily the same as those faced by ethnic minorities. An example is access to tertiary education, where ethnic minorities (particularly blacks in the United States and Malays in Singapore) continue to be severely disadvantaged, while women have made great advances (Gamoran, 2001).

In Singapore, gaining a tertiary education used to be a highly gendered phenomenon: boys were more likely than girls to be highly educated as it was assumed that men went out to work, while women stayed at home (Low, 1993). But this trend has changed over time. Women are now as educated as men, and many have gone into paid work. The introduction of the Women’s Charter in 1961, the growth of the industrial and service sectors in Singapore, the giving of generous state subsidies for tertiary education and the growing wealth of families, have all resulted in women having greater access to education today.

The disadvantages of women in Singapore lie in other areas -- most significantly in the domains of work and home. Despite substantial increases in female labour force participation over the past decades, gender role expectations continue to ensure that working women with young children bear the bulk of family duties and household chores. Women are less likely than men to be in paid work and when they work, are less likely to be in professional, managerial and technical (PMT) occupations.

The patriarchal state in Singapore has endorsed the reproduction of the gender script to a great extent. For example, the state has for some time in its history, placed a cap on the number of females in its local medical school, so that women comprised only a third of all medical students. The state reasons that it is less worthwhile to train women doctors as it assumes that they would, sooner or later, drop out of the paid workforce due to childcare. Such policies reflect gender discrimination not only because potential women doctors are excluded from training, but also because it reinforces the message that women should not aim their sights on such a good career (Lazar, 2001).

The state stipulates that men should be heads of their household and women should be supporters of the family. This belief is translated into policy. The allocation of medical benefits in the state sector serves as an appropriate example: male employees in the state sector may claim benefits for their families, while family members of female employees do not have access to similar benefits (Lazar, 2001). The point (of such a

36 policy) is with reinforcing the notion that it is the husband’s responsibility to look after the family’s economic needs. The husband-as-breadwinner model has made it more culturally acceptable for wives to stay at home (as homemakers) than it is for husbands to do so.

Elitism, racialization and patriarchy despite meritocracy

Meritocracy gives the impression that opportunities are equal across the board and that differences are only post-competition differences. However, in practice, pre- competition opportunities are seldom ever equal in the first place. Indeed, a meritocracy dispenses rewards based on personal achievement, but it cannot ensure that starting lines are equal for everyone.

As education is so essential to meritocracies, and as educational resources are so closely linked with class resources, the winners in an advanced merit-based system are increasingly individuals from the upper classes (Lareau, 2000). The logical end of meritocracy is elitism (Young, 1958). Elitism underscores the plight of homogeneously poor social groups such as the minority Malays in Singapore. Of course, ethnic inequalities do not operate through class mechanisms alone, but race is an important variable in its own right and a salient principle that continues to structure societies independent of class (Omi and Winant, 1994).

Concerning gender, women continue to experience substantial disadvantages in the realms of home and work, where the segregation of gender roles is pertinent. As noted by Hans Rosling, a noted Swedish international health professor and public statistics advocate who spoke recently at the UBS Philanthropy Forum (held in Singapore), the low fertility rate in Singapore (currently at 1.23 babies per woman) may not be due to the alleged lack of financial resources among young people, but because of “the not very advanced state of Singapore’s gender relations, which lags behind its economic and social development”. That is, “fathers... are not rising to the task of child-rearing,

37 and state support for equal parenting roles is not adequate.” As a result, “women have been saying “no” to babies.” (Straits Times, 12 May 2010).

To sum up, one could say that while the main disadvantages faced by ethnic minorities (e.g. Malays) are in family background inequalities and subsequently educational inequalities, the main disadvantages faced by women are in the realm of gender roles, reflected thus in women’s over-involvement in family and under-engagement in more prestigious forms of paid work. Gender groups may divide along class lines, but arguably more so in later stages of the life course than in earlier parts: that is, in careers rather than in class-at-birth (Smith-Lovin and McPherson, 1993; England, 1994; James, 2008). The nature of gender and ethnic inequalities may be expected to differ across societies, and each society’s gender and ethnic relations will have to be studied in detail. The arguments made in this paper apply strictly to Singapore.

Next chapters

The following chapters will illustrate how the aforementioned structural conditions of meritocracy, elitism, patriarchy and racialization affect the distribution, role and value of social capital in Singapore. Having provided a brief history of Singapore society, I now proceed to demonstrate, through each of my three papers, the inextricable link between contextual factors, social capital and job success more broadly.

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Chapter 3 (Paper 1) Categorical Sources of Varieties of Network Inequalities

Gender and ethnic groups do not just have unequal access to social capital; they have unequal access to ‘distinctive forms of’ social capital. Using survey data from Singapore, I show that whereas Chinese (relative to Malays and Indians) tend to have greater access to forms of social capital such as well-educated, wealthy, Chinese and weak tie social capital (but not male or non- kin social capital), men (relative to women) tend to have greater access to forms of social capital such as male, non-kin and weak tie social capital (but not well-educated, wealthy and Chinese social capital). These distinctive patterns of network inequalities may be explained by the distinctive patterns of access that gender and ethnic groups have to organizations such as schools, paid work and voluntary associations. Broadly, this paper draws attention to why and how ascriptive categorical forms of stratification (such as gender and ethnicity) produce such characteristic forms of network inequalities.

INTRODUCTION

The idea of social capital is that people have potential access to important resources based on their ties to others who have such resources (Lin, 2001). While it is widely recognized that social capital tends to be unevenly distributed in populations, along categorical lines such as gender and ethnicity (Lin, 2000), what is less clear is how gender and ethnicity -- as social categories rather than as individual attributes (or innate dispositions) bring about network inequalities.

Whereas biological explanations have been offered for gender and ethnic stratification (which some see as being natural and immutable), sociologists have generally sought to replace genetic interpretations of gender and ethnicity with social and categorical explanations (e.g. Shibutani and Kwan, 1965; Omi and Winant, 1994; West and Fenstermaker, 1995). While the study of gender and ethnicity as categorical processes is not new, the study of how gender and ethnic divisions bring about distinctive patterns of network inequalities remains relatively unexplored.

It is not hard to notice in the literature, that whereas gender inequalities in social capital tend to be discussed in terms of men’s and women’s unequal access to forms of social capital such as non-kin (Moore, 1990), weak ties (McPherson and Smith-Lovin, 1982) and men (Erickson, 2004), ethnic inequalities in social capital tend to be discussed in terms of ethnic groups’ unequal access to forms of social capital such as occupations (e.g. doctor, lawyer, cashier) (Moren-Cross and Lin, 2008), well-educated contacts (Wilson, 1987) and dominant ethnic groups (also Moren-Cross and Lin, 2008). And yet this –- the fact that gender and ethnicity tend to be associated with distinctive types of social capital is seldom pointed out, problematized or further theorized.

Using the case of a gender and ethnically-stratified society, Singapore, this paper demonstrates an instance of distinctive patterns of network inequalities by gender and ethnicity. Its task is to explain why -- whereas Chinese (relative to Malays and Indians) tend to have greater access to forms of social capital such as well-educated, wealthy and Chinese networks (but not men or non-kin), men tend to have greater access to forms of social capital such as men, non-kin and weak ties (but not well-educated, wealthy and Chinese networks). Or to pose the question more formally: Why and how do ascriptive categorical forms of stratification (such as gender and ethnicity in this case) produce such characteristic forms of network inequalities?

GENDER AND ETHNICITY AS SOCIAL CATEGORIES

More than individual attributes, sociologists have emphasized the role of gender and ethnicity as social divisions that organize everyday life. Already at birth, gender and ethnic categories form important bases for stratification because people believe them to be natural divisions of mankind (Shibutani and Kwan, 1965:46). While a person may acquire the culture or behaviour of an alternative group, he/she usually continues to carry the physical marks of his/her sex and ancestry and these become the basis of

further social distinctions and resource allocations (Shibutani and Kwan, 1965:51; Tilly, 1998; Ridgeway, 2006; Wimmer, 2008).

Gender and ethnicity are unique stratification systems in their own right, which are not ultimately reducible to class (Blumer, 1958; Grabb, 1984; West and Fenstermaker, 1995; Ridgeway, 2006). Certainly, while gender and ethnicity may be correlated with achieved characteristics such as educational attainment, job experience and skills, the persistence of pure gender and ethnic effects after controls testifies to the independent effects of social categories (England, 1994; Downey, 2008).

Gender and ethnicity are, as Tilly (1998:83) notes, “exterior categories” that constitute independent bases for discrimination practices. “Almost everywhere on earth... exterior categories such as male versus female, white versus black or citizen versus foreigner “provide scripts so pervasive that they modify interactions within all sorts of organizations...” (Tilly, 1998:79) These scripts refer to the common understandings, meanings, practices, relations and memories that are tied to categories. Durable inequalities occur when exterior categories such as “male” and “female” are imported and unquestioningly conjoined with interior categories such as “boss” and “secretary” by powerful organizational gatekeepers. Over time, the “male boss” and “female secretary” combination get adopted as an organizational template and repeated from office to office.

Using Tilly’s ideas, this paper presents an opportunity to think about how gender and ethnicity, as exterior categories, affect gender and ethnic groups’ access to organizations such as schools, paid work and voluntary associations, and how this subsequently affects their access to social capital.

The life course as a framing device

The life course serves as an excellent starting point for thinking about issues of gender and ethnic inequalities in social capital. To begin, the life course can be perceived as a path or road on which people travel. With time, these paths and roads form structured patternings of life course events, life transitions, turning points, and trajectories (Wheaton and Gotlib, 1997). An important aspect of categorical stratification and the life course is social groups’ uneven access to important organizations and life experiences such as school, work, marriage, parenthood, privileged households and voluntary associations (Macmillan, 2005). Depending on the class, gender and ethnic category, a person’s rate of participation in such organizations and life events may be expected to vary (Levy, 1996; Jackson and Berkowitz, 2005; Mayer, 2005).

At birth, the family organization is a pivotal site of intense early socialization and nurturing. This early socialization is typically followed by schooling (which itself consists a range of formal educational sequences: kindergarten, elementary school, high school, technical schools, college, etc). Schooling is typically followed by being in paid work, setting up a new family unit (i.e. marriage and parenting), joining voluntary associations, entering retirement, raising grandchildren, and so on. Most life courses are organized around more or less clearly established patterns of modal sequences with a tendency towards life course standardization amidst some de-standardization, especially in the area of family formation (Levy, 1996; Shanahan, 2000; Bruckner and Mayer, 2005).

Throughout the life course, organizational settings are not just places to accomplish tasks (e.g. get a university degree or get paid for work), but also places that supply multiple opportunities to form social capital. Schools, workplaces and voluntary associations are all contexts that facilitate social encounters and interactions, which potentially develop into relationships (Feld, 1981). The formation of social capital is often an iterative process: as people move through the life course, networks evolve as

new members are added and as others move away (Bidart and Lavenu, 2005). Often, networks become bigger and more diverse with time and experience (Fischer, 1982; Erickson, 1996).

Organizations employ gatekeepers to assess personal biographies in accordance with normative and institutionalized standards (Heinz, 1992). These gatekeepers (e.g. state, teachers, employers and other authority figures) act on behalf of organizations and are agents, whether conscious or not, of the reproduction of unequal life chances among social groups (Omi and Winant, 1994; West and Fenstermaker, 1995).

In North American schools, teachers reproduce ethnic inequalities by relying on racial categories in the allocation of rewards. Some ethnic groups do better, not because of their coursework mastery per se, but because teachers perceive the racial group to be diligent (Farkas et al., 1990). Concerning gender, bosses (who often are males), have relied upon gender stereotypes to allocate work: for example, let the “men” (who are assumed to leaders) be “managers” and let the “women” (who are assumed to be nurturers) be “secretaries”. This practice of matching exterior gender categories with interior rankings gets replicated across many work organizations (Tilly, 1998).

In general, we may think of organizations and their gatekeepers as upholding two broad kinds of inequality mechanisms: 1) unequal access to organizations and 2) unequal benefits for those who gain access to those organizations. The first implies mechanisms which result in individuals’ differential access to organizations. The second implies mechanisms which cause organizations to add resources unevenly to individuals and social groups. While several studies have looked at organizational sources of social capital (e.g. Erickson, 2004; Bian, 2008; Small, 2009), few have enquired into the extent to which organizations generate social capital unequally among categories of individuals.

Gender and ethnicity as unique categorical systems

Gender and ethnicity are unique categorical processes. Take contemporary changes in education for example: studies in the United States show that whereas gender inequalities in educational attainment have narrowed substantially over time, ethnic inequalities in educational attainment (especially between blacks and whites) have continued to be extremely salient (Gamoran, 2001). The question is why ethnicity has not followed the same progressive path of gender. A broad answer is that gender and ethnicity are governed by different dynamics (see Gamoran, 2001:140). In this paper, the unique dynamics of gender and ethnicity are reflected in gender and ethnic groups accessing distinctive forms of organizations and thereby accessing distinctive forms of social capital.

An instance of gender dynamics

The post World War II era of economic consolidation and the feminist movement in the United States created an atmosphere urging for greater gender egalitarianism in access to education and jobs. By the 1970s, girls were outclassing boys at school (Abbott, 2006), and women were actively engaging in paid labour markets (Blau and Kahn, 2006). But growing gender egalitarianism did not, by any means, eradicate gender inequalities.

While labour force participation rates among women are high, women still have much lower access to professional and managerial jobs compared to men, and tend to concentrate in female occupations such as clerical and non-commission retail sales, manufacturing jobs in non-durable goods and domestic and child-care work (England, 2006:246). Also, while the gender wage gap has closed considerably over the past three decades, men still earn more than women (Blau and Kahn, 2006).

Despite the modern era, the cultural mandate of “home” being the domain of “women”, and “work” being the domain of “men”, remains strong (Coser, 1991). Women’s significantly greater involvement in child-rearing has often led to many women leaving the workplace temporarily and losing out on opportunities to build up work experience and skills (Blau and Kahn, 2006). Unfortunately, whereas many women have gone out to the workplace, men have not gone domestic at an equivalently fast pace, resulting in working mothers having to cope with a second shift of unpaid work (Hochschild, 1989).

The bottleneck in gender inequality is thus driven by the fact that families continue to organize along the lines of gender (especially the assignment of child-rearing responsibilities to women), as well as the general resistance of men to taking on traditionally female activities in the household (England, 2006). The result is that while modern women are well-educated, many have, because of gendered expectations, stayed at home, particularly during the child-rearing years.

An instance of ethnic dynamics

Ethnicity is a different sort of inequality mechanism from gender. As Tilly (1998:82) notes: “...in much of our world, race and class overlap far more than gender and class, with the result that importing a gender boundary line has different consequences than importing racial frontiers.”

A major aspect of ethnic inequalities in modern societies such as the United States is ethnic minorities’ persisting disadvantages in the field of education. While the civil rights movement in the United States has certainly caused a dramatic reduction in overt racial discrimination, the gap in educational achievement between whites, blacks and Hispanics (but not Asians) continues to be obvious (Kao, 1995). Whereas educational inequalities have narrowed considerably between boys and girls, they remain persistent among ethnic groups, especially between blacks and whites (Gamoran, 2001).

It is not that blacks are opposed to education. Indeed, blacks value education as much as whites. The disadvantages of blacks in education are substantially due to the fact that “black youth’s strategy for success is less detailed, less complemented by daily routines”... and their route to success may often “be overwhelmed by skills, habits and styles” which do not match with the dominant culture (Downey, 2008:121). As family background is a strong predictor of educational resources (Lareau, 2000), poverty among blacks strongly limits their academic success (Downey, 2008).

In sum, contemporary societies have been characterized by two general trends reflecting the unique dynamics of gender and ethnicity. The first is the narrowing of gender but not ethnic differences in educational opportunities and attainment. The second is the substantial narrowing of gender differences in educational attainment, but not in the areas of family and paid work (Gamoran, 2001). Both these trends point to the distinctive categorical work of gender and ethnicity and can be meaningfully evoked to account for why gender and ethnic categories tend to generate such distinctive forms of network inequalities.

HYPOTHESES

I test four hypotheses:

H1: Dominant gender and ethnic groups have more social capital than less dominant gender and ethnic groups.

H2: Gender and ethnic groups access distinctive forms of social capital.

H3: Gender and ethnic groups access distinctive forms of social capital because they access distinctive forms of organizations.

H4: Organizations such as schools, paid work and voluntary associations generate social capital unequally, depending on gender and ethnicity.

Singapore serves as an excellent fieldsite for testing these hypotheses because gender and ethnic mechanisms are seen clearest in societies with strong forms of gender and ethnic inequalities and boundaries. As a highly patriarchal and racially-stratified society, Singapore is an appropriate case study for examining how gender and ethnicity work as general categorical processes in contemporary society.

SINGAPORE CONTEXT

In Singapore as in the United States, gender and ethnicity are important social divisions with significant consequences for stratification.

Concerning gender -- although mass education and industrialization have opened up educational and work opportunities for men and women beginning from at least five decades ago (Chang, 1995), many Singaporean women are still homemakers. In 2005, only 56.6% of women were in paid work, much less than the 78.2% among men (Department of Statistics, 2005). Lazar (2001) argues that the opening up of labour markets in Singapore does not actually reflect a real desire on the part of the state to grant women equal rights: the state needs the labour of women to grow the economy, but when the economy turns down, it is women who leave first.

At work, many women are in clerical or service jobs, serving a mostly male sector of CEOs, professionals and middle managers, even as a segment of lower-educated men concentrate in blue-collar jobs. In Singapore households, women still shoulder the majority of child-rearing and household chores (although many have foreign domestic workers to help lighten the load). Whereas many mothers have gone into the workplace (to supplement the household income in an increasingly expensive Singapore), men are still reluctant to contribute more actively to child-rearing, leaving the task primarily to wives and grandparents.

Working mothers are under stress in Singapore. On one hand, the state wants the paid labour (especially educated labour) of women to expand the economy. On the other hand, the state also wants women to be active in reproducing the next generation. The declining birth rate, especially among the Chinese and well-educated, has elicited a particular response from the state. According to Lee Kuan Yew,

Equal opportunities, yes, but we shouldn’t get our women into jobs where they cannot, at the same time, be mothers… You just can’t be doing a full-time heavy job like a doctor or engineer and run a home and bring up children.

(Lee Kuan Yew, Straits Times 15 August 1983, cited in Chan, 2000:50).

The patriarchal state thus curtails women’s more active participation in paid work. The cultural mandate (Coser, 1991): that work is the domain of men and home is the domain of women is a categorical mechanism that continues to undercut the life chances of women (especially older women) in Singapore.

Concerning ethnicity -- the roots of Singapore’s racial social structure lie in the British colonial application of racial ideology in the administration of a multiethnic population (Hirschman, 1986). One historical outcome of racial rule was an economy based on a racial division of labour with Chinese as traders, Malays as land cultivators and Indians as plantation workers, and above all, a society characterized by racially-segregated housing.

As Chinese immigration from the mainland grew due to trade, the Chinese population soon superseded the indigenous Malay population. As colonial fortunes grew, so did Chinese wealth and population. A racial stratification order was soon established: the colonizers on top, followed by Chinese, Indians and Malays in tow. After the second world war, when the British withdrew, the Chinese moved up the vacancy chain (White, 1970), with Indians and Malays following behind.

Today, Chinese power permeates the various spheres of economy, politics, education, and culture in Singapore, leaving the ethnic minorities, particularly Malays, in positions of significant disadvantage (Rahim, 1998; Lee, 2006). To be sure, there are many poor Chinese in Singapore (that is, ethnicity crosscuts class among the Chinese), but simply “being Chinese” has status benefits. If Blumer (1958:4) is right that people tend to perceive of ethnicity in categorical terms: that is, as a “sense of group position”, then belonging to the dominant ethnic group is important, independent of class.

An important aspect of ethnic stratification in Singapore is Chinese’s and Indian’s disproportionately greater access to higher education. In 2000, 12.6% and 16.5% of Chinese and Indians were university graduates, while only 2.0% of Malays were university graduates (Lee, 2006). The educational advantages of Chinese and Indians may be due to several factors:

First, Chinese and Indians are much more likely than Malays to come from privileged family backgrounds. The 2000 Census of Population revealed stark differences in the median monthly household incomes of ethnic groups: Chinese households earned a median monthly household income of $3,848, Malays: $2,708 and Indians: $3,387. That family resources are such important determinants of educational access in contemporary societies (Lareau, 2000), will help to partially account for why the richer Chinese and Indians are more educationally advantaged than the poorer Malays.

Second, education is highly valued in the Chinese and Indian cultures. During the period of the dynasties, formal examinations were an integral part of state administration in the Chinese mainland. There was a highly pragmatic side to the education, in that examinations were being mobilized as a means to select the most competent administrators for the emperor’s service. The practice of education in Singapore mirrors this ancient Chinese model. Today, a rigorous examinations process selects the best candidates for the most influential jobs in the state sector. Rigorous

private tuition regimes have become the norm among Chinese families. Meanwhile, children are increasingly seeking psychiatric help to cope with examination pressures.

Third, Chinese use education to hoard opportunities for themselves with the elite Special Assistance Plan (SAP) schools being a major categorical tool in this regard. As SAP schools teach both English and Mandarin as first languages, they inevitably exclude many Malays and Indians. The mission schools are another categorical mechanism. Large and influential networks among alumni ensure the sustained channeling of wealth and resources into mission schools. These schools select students based on legacy admissions and as mission schools are Christian schools, Malays (who mostly are Muslim) do not attend.

To exacerbate matters, Malays (and to a lesser extent, Indians) have to contend with unfavourable stereotypes being levelled against their racial category. Primary school textbooks have often portrayed ethnic minorities as being in less prestigious work such as “bus driver” or “housekeeper” for Malays and “zookeeper” or “policeman” for Indians. By contrast, Chinese are represented favourably as “teachers”, “doctors” and “principals” (Barr, 2006)!

DATA AND MEASURES

Data sources

I rely on personal network data from the Project Network Survey conducted in Singapore between February and July 2005. The valid sample size is 989 Singapore citizens and residents aged between 25 and 55 years. While there are several national surveys in Singapore which focus on community development and relations (e.g. Housing and Development Board, 2000; Ministry of Information and the Arts, 2000; Department of Statistics, 2001), this is the first study which aims specifically at describing the personal networks of Singapore citizens and residents in substantial detail. The data was

collected by a reputable and experienced survey research company, AC Nielsen, and conducted in three languages, English, Mandarin or Malay, whichever suited the respondent. Most of the interviews were administered by middle-age women as they are often perceived to be less threatening than males or younger interviewers (see Lang and Secic, 2006). Each interview lasted about an hour, and was conducted at the door of the respondents’ homes.

Social capital measures

As in Fischer’s Northern Californian study (Fischer, 1982), I utilized a range of some fourteen name generators (see Appendix A) to delineate the names, followed by name interpreters enquiring about each name and the nature of his/her relationship with the respondent.

The name generators were designed to cover a range of emotional, social and instrumental scenarios, with the exact wordings modified to suit the Singapore context. The name interpreters collected information such as the gender, ethnicity, age, housing type and education level of the named alters, as well as the nature of the role relationship and other tie characteristics (Marsden, 2005).

I used six measures of social capital and define each kind of social capital as the number of network members who have a certain potential resource. These include: 1) number of university graduates, 2) number of wealthy home owners 3) number of Chinese 4) number of men 5) number of weak ties and 6) number of non-kin.

Each type of social capital represents potential access to specific kinds of resources: 1) educational attainment is an important marker of social prestige and resources in many contemporary societies. The well-educated have greater access to all kinds of material, cultural and symbolic resources, 2) personal wealth is likewise a powerful resource. Economic capital is a magnet for other kinds of resources, including social capital,

economic and social honour (Bourdieu, 1984), 3) Chinese ethnicity represents a significant source of symbolic power in Singapore. As the ruling ethnic group, being “Chinese” is a form of social power independent of class, 4) ‘male’ is another potentially important resource given the highly patriarchal nature of Asian societies where men are more likely than women to control valuable resources (Lai, 2008), 5) weak ties are important pathways to novel and influential resources because of their boundary- spanning nature (Granovetter, 1973; Lin, 1982), and 6) non-kin are important to the extent that novel resources such as job information are typically found outside kinship circles (Granovetter, 1973; Portes and Sensenbrenner, 1993).

Table 1 reports the types and amounts of each social capital by gender and ethnicity. I rely mainly on OLS and negative binomial regressions to estimate the sources of the respective kinds of social capital. My strategy consists of adding variables (representing sources) in the sequence of a typical life course and noting the changes in gender and ethnic coefficients.

While all the measures of social capital are based on count data, some of the distributions are more skewed than others -- for example, the distributions of university graduates, private housing dwellers and weak ties are highly skewed to the right (with variances far exceeding the means), implying the need for negative binomial regressions instead of the more conventional OLS. By contrast, the distributions of male, Chinese and non-kin social capital were much less skewed. A square-root transformation was applied to these distributions to make them more normal before proceeding with OLS regression.

TABLE 1. NUMBER OF TYPES OF SOCIAL CAPITAL BY GENDER AND ETHNICITY Male Female Male/ Chinese Malay Indian Chinese SOCIAL CAPITAL Female /Malay diff. diff.

Number of university 1.02 .99 ns 1.24 .21 1.00 *** graduates

Number of private 1.02 1.16 ns 1.38 .33 .79 *** housing dwellers

Number of Chinese 4.63 4.18 * 5.98 .95 1.30 ***

Number of men 4.53 1.77 *** 3.07 2.66 3.04 *

Number of weak-ties .76 .48 *** .69 .39 .46 ***

Number of non-kin 4.10 3.32 *** 3.70 3.41 3.87 ns

*P < .05 **P < .01 ***P< .001

Causes of social capital

Keeping with a life course approach, I entered the independent variables in a step-wise sequential manner, beginning with ascribed characteristics: gender, ethnicity and age, followed, by achieved characteristics: education, work, household income, family formation, and voluntary associations, one at a time.

Gender is a dummy variable, with female assigned ‘1’ and men: female = 0. Ethnicity is represented by two dummy variables: Chinese and Indian, with Malay as the reference category. Age is entered in linear and quadratic forms, since research indicates that social involvement tends to increase with age, peaks at middle life, and declines in the later years (Mirowsky and Ross, 1999).

Education is entered as two dummy variables: ‘middle’ education and ‘high’ education. The middle education category comprises respondents with at most secondary school education, vocational training, or junior college qualifications. The high education

category comprises respondents with polytechnic or university degrees. The reference category, ‘low’ education, comprises respondents with at most some secondary school education.

Work is entered as a dichotomous variable, distinguishing between respondents in paid work and non-paid work. Like education, work is an important milestone in the life course. Work represents new opportunities to meet others and build social capital extending beyond school and kin. Unfortunately, paid employment is unequally distributed in the social structure. In Singapore, women, despite having comparable levels of education as men, are still more likely to remain at home, due in no small part to the persistence of gender role ideologies in contemporary society (Coser, 1991).

Household income refers to the income of all household members combined. There were 46 missing cases, but this is small relative to the total sample size of 989. As with typical income distributions, there was a noticeable positive skew. A square root was applied to the seventeen levels of the variable in order to make the distribution more normal.

Family formation is represented by two dummy variables: ‘married’ and ‘kids less than 18 years’. Marriage and parenthood are important stages in the life-course with significant consequences for social relationships (Moore, 1990). Marriage increases kin commitment substantially as the couple and their two families become linked through the marital bond (de Vries, 1996). Kin involvement increases even further when children arrive, especially for women: as noted by Jacobs (1988 cited in McPherson and Smith-Lovin, 1993:245), “childbearing may (often) represent a network bottleneck sending men and women into very different structural career streams”.

Participation in voluntary organizations is entered as a dummy variable, denoting whether or not the respondent is a member of any voluntary organization. 32% of

respondents indicated being part of at least one voluntary organization. A clear majority of the participation was in religious groups (e.g. small groups in churches or Islamic religious classes) with a scattering of participation in associations such as charity organizations, country clubs, sports associations, ethnic organizations, special interest groups, neighbourhood associations, parent-teacher associations, and professional organizations. I did not use number of associations as my measure of social participation, since only a few respondents (less than 7%) participated in more than one association.

The relatively low participation in voluntary organizations in Singapore can be explained by at least two factors: first, the small geographical size of Singapore along with its highly efficient and interconnected transport system makes it relatively easy to rely on kin relations rather than on civic relations. Second, the short and shallow history of democracy in Singapore potentially limits the growth of its voluntary associations, and reciprocally, the weakness of voluntary associations helps keep the level of democracy low (see Paxton, 2002). As compared to the United States, where the average number of voluntary association memberships per person is 1.98, the level of participation in voluntary associations in Singapore is very low: the average number of voluntary association memberships in this study is only .42, which is on par with countries like Japan (.49) and Romania (.42) (Table 1 in Curtis et. al., 2001).

Interaction effects

As organizational settings may be expected to generate social capital at different rates for different social categories (of people), the testing of interaction effects forms an important part of the analysis.

I focus on three organizational settings in particular: 1) higher education 2) paid work and 3) voluntary associations, and estimate the extent to which their effects on the six

types of social capital are modified by gender and ethnicity. The interaction terms were entered as follows:

Differential impact of institutional settings on varieties of social capital by ‘gender’: - [Middle education x Female], [High education x Female] - [Work x Female] - [Association x Female]

Differential impact of institutional settings on varieties of social capital by ‘ethnicity’: - [Middle education x Chinese], [High education x Chinese], [Middle education x Indian], [High education x Indian] - [Work x Chinese], [Work x Indian] - [Association x Chinese], [Association x Indian]

The omitted categories are low education (i.e. completed primary and some secondary school), male, Malay, not in paid work, and no involvement in voluntary associations.

I did not report the fine details of every model, as this would certainly overwhelm the reader (i.e. 36 regression models in total). Instead, I summarize the results using a ‘yes (if interaction effects are present) and no’ (if interaction effects are not present) format (see Table 8).

RESULTS

Gender and ethnic inequality in social capital

Table 2 presents findings on two levels. At the broad level, we see dominant gender and ethnic groups (i.e. men and Chinese) having more social capital than their less dominant counterparts (i.e. women, Malays and Indians).

At a more specific level however, we see distinctive patterns of network inequalities by gender and ethnicity: that is, women have lower access to men (- .83***), weak ties (- .44***) and non-kin (- .26***), but equivalent access to university graduates (.03), private housing dwellers (.13) and Chinese (- .11) relative to men, while Chinese have greater access to university graduates (1.79***), private housing dwellers (1.46***), Chinese (5.06***) and weak ties (.54***), but equivalent access to men (.07) and non-kin (.08), relative to Malays.

These broad and distinctive patterns of network inequalities are consistent with the first and second hypotheses, which state that 1) dominant gender and ethnic groups have more social capital than less dominant gender and ethnic groups (H1) and 2) that gender and ethnic groups tend to access distinctive forms of social capital (H2).

Categorical sources of gender and ethnic network inequalities

In subsequent regression models, I control for the effects of organizations and life course variables, beginning first with education (Table 3), then paid work (Table 4), then household income (Table 5), then family formation (Table 6), then voluntary associations (Table 7). Adding controls in a sequential manner will help us better understand how various organizations and life-course events contribute to the distinctive patterns of network inequalities we see.

Age

Contrary to the literature which reports a peak in social capital during midlife (Erickson, 2004), there is no such quadratic relationship between age (ranging from 25 to 55 years) and the kinds of social capital studied here. Instead, the association between age and social capital is linear and negative.

TABLE 2. CATEGORICAL INEQUALITY IN SOCIAL CAPITAL # university # private # Chinese # men # weak ties # non-kin graduates housing dwellers Predictors Female .03 .13 - .11 - .83*** - .44*** - .26*** Chinese 1.79*** 1.46*** 5.06*** .07† .54*** .08 Indian 1.54*** .90*** .35 .09 .17 .06 Age - .23*** .03 - .14** - .04** .04 - .06*** Age square - .03 - .03 - .05 .00 - .01 .02†

Constant - 1.57 - 1.14 1.11 1.97 - .67 1.82 R square/BIC 2517.25 2756.11 .55*** .36*** 2104.31 .06*** N 988 987 989 989 989 989

†p < .10 *p < .05 **p < .01 ***p < 0.001 Omitted categories: Male, Malay

Table 2 indicates that older cohorts are less likely than younger cohorts to have social capital such as university graduates (- .23***), Chinese (- .14**), men (- .04**) and non-kin (- .06***).

One reason is cohort differences in education. The opening up of mass education in Singapore beginning in the 1970s has benefited the younger cohorts in particular (Chang, 1995). As older cohorts belonged to a poorer, less developed era of Singapore’s history, they have had fewer opportunities to procure a good education.

With educational effects controlled for in Table 3, the effect of age on access to university graduates, Chinese, men and non-kin disappears, suggesting that the negative effect of age on social capital is driven primarily by older cohorts’ lower access to education. Furthermore, the effect of age on access to private housing dwellers changes from non-significant (.03 in Table 2) to highly significant (.19*** in Table 3), suggesting that it is indeed the lack of education among older cohorts that suppresses their access to wealthy social capital.

Education

Table 3 shows that higher levels of education are a substantial source of well-educated (2.97***), wealthy (1.78***), Chinese (.75***), men (.17***), and non-kin (.42***) social capital.

Controlling for education in Table 3, we see a sizable decline in the effects of Chinese and Indian on access to university graduates and private housing dwellers, suggesting that educational resources are a major factor explaining Chinese’s and Indian’s greater access to well-educated and wealthy social capital, relative to Malays.

The fact that ethnicity remains highly-significant at the .001 level, also suggests that there are other factors besides education that potentially explain ethnic inequalities in educated and wealthy social capital. To add, Chinese are much more likely to have Chinese networks, and again education explains some of this, but not completely. So what are some of these other factors?

First, dominant ethnic groups may generally find it easier to add valuable contacts to their networks because of the high social status of their ethnic group. Members from high-status ethnic groups may appear as attractive network members to others, and hence find it easier to add all kinds of individuals to their personal networks.

Second, ethnic culture plays an important role linking ethnically-similar individuals together. Having a shared ethnic culture facilitates ease of communication and becomes the basis upon which networks of social closure and ethnic homophily are established.

Third, controlling for education does not by itself equalize educational resources. A Chinese and Malay may be both high school graduates, but because Chinese goes to a better school, he/she ends up being in better social circles.

Notice that education does practically nothing to account for gender inequalities in access to men, weak ties and non-kin (Table 3), which suggests that gender inequalities in social capital are driven by factors other than education.

TABLE 3. EDUCATION AND INEQUALITY IN SOCIAL CAPITAL # university # private # Chinese # men # weak ties # non-kin graduates housing dwellers Predictors Female .10 .19† - .10 - .83*** - .43*** - .26*** Chinese 1.10*** 1.07*** 4.91*** .03 .52*** .01 Indian .93*** .49* .22 .05 .15 - .00 Age .02 .19*** - .07 - .02 .05 - .02 Age square .00 - .02 - .05† .00 - .01 .02†

Education (mid) 1.27*** .85*** .34* .03 .04 .27*** Education (high) 2.97*** 1.78*** .75*** .17*** .10 .42***

Constant - 3.03 - 1.93 .87 1.94 - .70 1.65 R square/BIC 2198.26 2622.12 .55*** .37*** 2117.65 .11*** N 988 987 989 989 989 989

†p < .10 *p < .05 **p < .01 ***p < 0.001 Omitted categories: Male, Malay, Education (low)

Access to paid work

With ascribed characteristics and education held constant, access to paid work is strongly correlated with access to non-kin (.26***). Controlling for work, the most noticeable changes (between Tables 3 and 4) are the reduced effects of female on access to weak ties and non-kin, suggesting that women’s lower participation in paid work is a very important factor accounting for their lower access to weak ties and non-kin.

Although men and women in Singapore have equal access to educational attainment, women lag behind men in labour force participation. This implies an inequality mechanism that suppresses women’s ability to convert their human capital into labour force participation. A salient source of female disadvantage is the persistence of gender

role ideologies emphasizing women’s ostensibly natural place in the home (and men’s ostensibly natural place at work).

TABLE 4. WORK AND INEQUALITY IN SOCIAL CAPITAL # university # private # Chinese # men # weak ties # non-kin graduates housing dwellers Predictors Female .14 .13 .08 - .81*** - .36** - .16*** Chinese 1.09*** 1.07*** 4.90*** .03 .51** .00 Indian .93*** .48* .20 .05 .13 - .01 Age .03 .18*** - .06 - .02 .06 - .02 Age square .00 - .02 - .04 .00 - .01 .02*

Education (mid) 1.25*** .88*** .25 .02 .00 .22*** Education (high) 2.94*** 1.83*** .61** .16** .05 .35***

Working .12 - .17 .51** .06 .20 .26***

Constant - 3.12 - 1.80 .49 1.90 - .85 1.46*** R square/BIC 2204.31 2627.19 .56*** .37*** 2122.48 .12*** N 988 987 989 989 989 989

†p < .10 *p < .05 **p < .01 ***p < 0.001 Omitted categories: Male, Malay, Education (low), not in paid work

Household income

With ascribed characteristics, education and work held constant, household income is associated with knowing more university graduates (.45***), private housing dwellers (.78***) and men (.09**) (Table 5). The most noticeable changes between Tables 4 and 5 are the reduced effects of Chinese and Indian on access to university graduates and private housing dwellers, suggesting that household resources are important sources of Chinese and Indians’ greater access to well-educated and wealthy social capital.

Household wealth may facilitate access to well-educated and wealthy social capital in several ways. First, wealthy individuals are likely to move around in privileged social circles, such as in elite clubs where they meet other advantaged people like themselves.

Second, wealthier people are more likely to live in private housing and may therefore meet other wealthy residents. Third, wealthier people enjoy higher levels of geographical mobility. As people travel far and wide, their networks are expanded through meeting others who are similarly privileged and geographically mobile.

TABLE 5. HOUSEHOLD INCOME AND INEQUALITY IN SOCIAL CAPITAL # university # private # Chinese # men # weak ties # non-kin graduates housing dwellers Predictors Female .05 - .02 .08 - .82*** - .34** - .16*** Chinese .90*** .77*** 4.90*** .01 .51** .00 Indian .83*** .21 .21 .04 .11 .00 Age - .01 .14*** - .06 - .02 .07† - .01 Age square .01 - .01 - .04 .01 - .02 .02*

Education (mid) 1.00*** .45** .18 - .03 .05 .20*** Education (high) 2.47*** .92*** .52* .06 .21 .34***

Working .01 - .23† .51** .05 .29* .26***

Household .45*** .78*** .14 .09** - .17† .02 income

Constant - 3.93 - 3.36 .15 1.70 - .52 1.41 R square/BIC 2061.95 2376.89 .56*** .38*** 2036.98 .13*** N 953 952 954 954 954 954

†p < .10 *p < .05 **p < .01 ***p < 0.001 Omitted categories: Male, Malay, Education (low), not in paid work

Family formation

There are two aspects of family formation that are of interest here: 1) being married and 2) having young children (less than 18 years). Both are significant turning points in the life course with important consequences for social relations. Table 6 indicates that other factors held constant, being married is associated with knowing less non-kin (- .13*), but knowing more men (.11*).

As marriage is normatively a time to focus on the family and devote energies to setting up and maintaining a household, access to non-kin may be expected to shrink. Concerning more men, research indicates that women are often kin-keepers and sometimes managers of their husband’s networks (Lai, 2008).

TABLE 6. FAMILY FORMATION AND INEQUALITY IN SOCIAL CAPITAL # university # private # Chinese # men # weak ties # non-kin graduates housing dwellers Predictors Female .06 - .03 .06 - .83*** - .36** - .16*** Chinese .87*** .77*** 4.90*** .01 .52** .01 Indian .75** .19 .25 .04 .17 .00 Age - .01 .14*** - .06 - .02 .08† - .01 Age square - .01 - .02 .00 .02* .00 .02*

Education (mid) 1.01*** .46*** .16 - .03 .03 .20*** Education (high) 2.50*** .93*** .54* .07 .17 .33***

Working - .02 - .25* .55*** .07 .29† .24***

Household .45*** .79*** .10 .08* - .14 .04 income

Married .16 - .03 .17 .11* - .24 - .13* Kids < 18 - .39** - .13 .41* .07 .37* .05

Constant - 3.75 - 3.24 - .23 1.60 - .67 1.44 R square/BIC 2066.11 2388.56 .57*** .39*** 2044.35 .13*** N 953 952 954 954 954 954

†p < .10 *p < .05 **p < .01 ***p < 0.001 Omitted categories: Male, Malay, Education (low), not in paid work, not married, no children below 18 years

Having children less than 18 years old is associated with having more weak ties (.37* in Table 6), which is an interesting result when juxtaposed against the earlier finding that marriage reduce relations with non-kin (- .13* in Table 6). It appears that whereas couplehood strengthens kinship boundaries, young children reopen parents to the outside world. Children are often brokers of relationships. Through their various activities such as childcare, school activities, private tuition and sports, children provide

parents with opportunities to know other parents and develop other kinds of weak ties (Erickson, 2004; Small, 2009).

Interestingly, having children (less than 18 years old) is associated with lower access to university graduates (- .39** in Table 6). One possible reason is that children require constantly available care, so parents may tend to concentrate more on helpers who are free to help and do not have the education: folks such as ‘grandma’ or ‘grandpa’. University graduates probably are too busy working (or caring for their own children) to be much use.

Voluntary associations

Social participation is positively associated with many kinds of social capital: well- educated social capital (.62***), wealthy social capital (.53***), Chinese (1.21***), men (.26***), weak ties (.45***) and non-kin (.51***) (Table 7). So why are voluntary associations such fertile ground for social relations? First, it could be that joiners of voluntary associations are generally more sociable or gregarious to begin with, and therefore are more likely to have diverse connections. Second, voluntary associations may often have institutional linkages with other organizations: for instance, the childcare centre that brings in the occasional stress management guru or elementary school application advisor for parents, thus allowing them to know people from outside the childcare centre itself (Small, 2009). Indeed, voluntary associations expand the reach of personal contacts and are significant sources of diverse ties for both men and women (Erickson, 2004; Bekkers et al., 2008).

The link between social participation and social capital may work in the reverse as well. As voluntary associations may often recruit members through the networks of existing members, having a large personal network increases one’s chances of being introduced

to a voluntary association. To better understand the nature of the associations/social capital link, future research using longitudinal data is needed.

With voluntary associations controlled for, the negative effect of female on weak ties and non-kin becomes stronger (i.e. more negative), suggesting that women’s more active participation in voluntary associations (very data verifies this), alleviates their lack of social capital.

TABLE 7. VOLUNTARY ASSOCIATIONS AND INEQUALITY IN SOCIAL CAPITAL # university # private # Chinese # men # weak ties # non-kin graduates housing dwellers Predictors Female .01 - .07 - .04 - .85*** - .42*** - .20*** Chinese .98*** .85*** 5.08*** .05 .62*** .09 Indian .75*** .19 .16 .02 .13 - .03 Age - .05 .11*** - .13** - .03** .05 - .04** Age square - .02 - .02 .00 .02* .00 .02*

Education (mid) .94*** .40** .02 - .06 - .03 .14** Education (high) 2.39*** .78*** .24 .01 .03 .21**

Working - .02 - .25* .55*** .07 .28† .24***

Household .41*** .78*** .07 .07* - .16 .02 income

Married .20 - .02 .18 .11* - .24 - .12* Kids < 18 - .43*** - .16 .37* .06 .36* .03

Associations .62*** .53*** 1.21*** .26*** .45*** .51***

Constant - 3.88 - 3.37 - .41 1.56 - .75 1.36 R square/BIC 2037.68 2366.30 .60*** .42*** 2038.39 .23*** N 953 952 954 954 954 954

†p < .10 *p < .05 **p < .01 ***p < 0.001 Omitted categories: Male, Malay, Education (low), not in paid work, not married, no children below 18 years, No participation in voluntary associations

Another noticeable change when voluntary associations is held constant, is that the positive effect of Chinese on access to university graduates, private housing dwellers, Chinese and weak ties becomes stronger, suggesting that Chinese’s lower participation in voluntary associations (my data verifies this) suppresses their access to social capital. Chinese have lower rates of participation in voluntary associations because they are less likely than Malays and Indians to be part of religious associations. Practically all Malays are (mosque-going) Muslims, and most Indians are either Muslims or Hindus. Chinese are Buddhists, Christians, or Taoists, but many are free-thinkers and therefore not affiliated with any religion or religious associations.

Interactions

To the extent that organizations such as universities, paid work and voluntary associations generate social capital unequally across gender and ethnic groups, categorical inequalities are being reproduced. Yet more than that, by testing interactions, we are also interested to see if organizations have effects beyond the powerful effects of access.

Higher education: Table 8 indicates that the relative effect of education on social capital does not differ by gender or ethnicity. That is, education is an equally efficacious generator of social capital, regardless of whether the person is male or female, Chinese, Malay or Indian. Hence, the primary mode of network disadvantages among ethnic groups appears not to lie in high education producing more social capital for some ethnic groups than others, but in ethnic groups having unequal access to high education, more primarily.

Paid work: Women are as likely as men to gain social capital from participation in paid labour. As is the case for ethnic minorities and education, this finding suggests that women’s deficits in social capital arise more fundamentally from their lower access to

paid labour markets, rather than from paid labour markets working more efficaciously for men. Being in paid work also generates social capital equally well for ethnic groups. Except for some marginal evidence that paid work generates non-kin social capital more efficaciously for Indians (.29†), the majority results indicate a clear pattern of equal relative payoffs by ethnic group. These general results are rather surprising, given that there are such large gender and ethnic differences in the kinds of work people do. As my data is based on name generators and therefore closer ties (Marin, 2004), it may not have successfully captured the much broader set of weak and influential ties that work and occupations help generate.

Voluntary associations: Women are especially likely to gain on weak ties (.39†) and non- kin (.23**) when they join voluntary associations, suggesting that voluntary associations are strong compensation mechanisms for women. It appears that women’s lower access to paid work is freeing their time for participation in voluntary associations.

Voluntary associations are especially likely to increase Chinese’s access to other Chinese (1.29***). One plausible reason is the ethnically homogeneous nature of many voluntary associations in Singapore, especially religious organizations (such as churches and Chinese temples). Also, as Chinese form the majority of residents in Singapore (75%), the likelihood of having ties to Chinese rather than Malays or Indians is higher by virtue of demography (Blau, 1977).

Interestingly, while voluntary associations are especially likely to increase Chinese networks among Chinese (1.29***), they are especially unlikely to increase Chinese’s access to weak ties (- .93**) and non-kin social capital (- .19†). These significant interactions may be interpreted in another way and that is, voluntary associations are especially likely to increase weak ties and non-kin among Malays (since it is the omitted category). In sum, voluntary associations are especially useful generators of social capital, not only for women, but for ethnic minorities as well.

DISCUSSION

Ascriptive categorical forms of stratification such as gender and ethnicity produce distinctive forms of network inequalities. The case of Singapore illustrates that whereas men tend to have more social capital such as men, weak ties and non-kin (but not university graduates, private housing dwellers, Chinese and weak ties), dominant ethnic groups tend to have more social capital such as university graduates, private housing dwellers, Chinese social capital and weak ties (but not men and non-kin).

These distinctive patterns of access to social capital are a function of gender and ethnic groups’ distinctive patterns of access to various types of organizations such as schools, paid work and voluntary associations. My data illustrates that ethnic groups’ unequal access to education (but equal access to paid work) and gender groups’ unequal access to paid work and voluntary associations (but equal access to education) account for much of why men and women, Chinese, Malays and Indians tend to have such distinctive forms of social capital (i.e. H3).

Certainly, the exact nature of the links between ascriptive categorical forms of stratification, organizational access and social capital will be expected to differ depending on the specific conditions of societies. In Japan, for example, men continue to outnumber women in colleges and universities (see Brinton, 1992:86). And in the United States, blacks continue to be greatly disadvantaged in education, while some minority groups such as East Asians have excelled (Kao, 1995). In other words, there will be variations in the characteristic types of social capital that gender and ethnic groups have access to, depending on societal variations in gender and ethnic groups’ access to organizational settings where social capital is formed.

So why have educational inequalities narrowed so considerably for men and women, and yet remained so salient among ethnic groups in contemporary society? One reason

is that in modern societies, educational achievement remains highly-correlated with race and socio-economic background (Lareau, 2000). While mass education has opened up the educational landscape for many people, parental resources still play an extremely important role determining who the eventual winners and losers are in the education race. Well-to-do families have clearly an upper hand as elite parents are able to impart to their children the relevant cultural codes needed for successful education, hire private tutors, and maintain libraries of information at home. In contemporary times, it is ethnic minorities rather than girls who are especially disadvantaged in this area of household wealth and family privilege (Gamoran, 2001).

TABLE 8. SUMMARY OF INTERACTION EFFECTS Does Does Does Does effect of working on Does effect of associations on Does effect of associations on effect of effect of effect of social capital vary by social capital vary by social capital vary by ethnicity? education education working ethnicity? gender? on social on social on social capital capital capital vary by vary by vary by gender? ethnicity? gender?

Type of social capital

# university No No No No No No graduates

# private housing No No No No No No dwellers

# Chinese No No No No No [association] x [Chinese] = 1.29***

# men No No No No No No

# weak ties No No No No [association] x [female] = [association] x [Chinese] = - .93** .39†

# non-kin No No No [working] x [Indian] = .29† [association] x [female] = [association] x [Chinese] = - .19† .23**

Omitted categories: Male, Malay, not working, no participation in voluntary associations †p < .10 *p < .05 **p < .01 ***p < 0.001

The opening up of mass education in 1960s, along with the establishment of the Women’s Charter in 1961 has considerably narrowed educational inequalities among men and women in Singapore. The heavy subsidization of tertiary education by the state and the growing wealth of families have ensured that households could now send both sons and daughters to the polytechnics and universities, and not just sons alone, as in a generation ago. While there continues to be gender discrimination in some areas of tertiary education (e.g. entry into medical school), the prospect of obtaining a university education remains high for women (in some cases, higher than men). Instead, it is in the area of paid work that gender inequalities are more salient, especially from the viewpoint of women’s significantly lower participation in paid work and their higher involvement in childcare.

The swift advancement of women in education has not been followed up by an equally swift progress in women’s access to paid work. One reason is the persisting gender script in contemporary societies, which fosters the categorical mindset that the place of men is work, while the place of women is the home (Coser, 1991). Today, women are still significantly less likely than men to be in paid work.

It is interesting that women and ethnic minorities experience their respective forms of network inequalities at different points in the life course. My data suggests that whereas women experience significant network disadvantages during the work/family formation stage of the life-course, ethnic minorities experience significant network disadvantages much earlier, during the education stage of the life course. Indeed, the experience of network inequalities among men and women and ethnic groups is bound up with such structural conditions such as gender scripts, ethnic categorization and life course sequencing.

While women often experience network inequalities stemming from their lower access to paid work, their greater participation in voluntary associations has helped alleviate

77 those network disadvantages to some extent. According to Table 8, women are especially likely to gain on weak ties and non-kin when joining voluntary associations. These findings illustrate that network deficits at one point in the life course can be compensated at other points in the life course.

On the question of whether organizations add social capital unequally to social groups, there appears to be a mixture of results. Most of the tests for interaction effects point to an absence of conditional effects, but there were some important instances of conditional effects – such as the heterogeneous impact of voluntary associations on access to weak tie, non-kin, and Chinese social capital by gender and ethnic groups (see Figure 8) (this grants some support to H4).

The general lack of conditional effects does not however imply the absence of categorical inequalities. Much of the gender and ethnic inequalities in social capital stem from gender and ethnic differences in access to organizations rather than in organizations rewarding some groups better than others.

There are other categorical factors besides organizational access and personal resources that possibly account for persisting network inequalities by gender and ethnicity. These include: 1) the effects of stereotyping (which make individuals from some categories more (and less) attractive as potential network members), 2) the different kinds of work gender and ethnic groups do, which affect networking opportunities and demands, and 3) the role of gender and ethnic homophily.

This paper has shown that distinctive patterns of gender and ethnic inequalities in organizational access and life course patterns produce correspondingly distinctive patterns of gender and ethnic inequalities in access to varieties of social capital. Without understanding the distinctive dynamics of ascriptive categorical forms of stratification at the level of social structure, organizations and the life course, we would

78 not understand the distinctive distribution of different kinds of social capital by social categories.

The nuanced nature of my results shows that when studying social capital, it is not enough to simply ask: “who has more (or less) social capital?” Instead, we need to ask: “who has more (or less) of what types of social capital and why?”

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Chapter 4 (Paper 2) Social Networks and Labour Market Outcomes in a Meritocracy

This paper examines the significance of personal contacts in job searches, in the context of Singapore’s meritocratic system. I show that in certain sectors, such as the state bureaucracy, social networking brings no distinct advantages as appointments are made exclusively on the basis of the academic credentials of the candidates. Thus, personal contacts are not always useful, especially in labour markets that rely heavily on the signaling role of academic credentials to match persons to jobs and allocate rewards. In contrast, personal contacts are more useful among less qualified job searchers in the private sector.

INTRODUCTION

We know that personal contacts are generally useful for getting jobs (Granovetter, 1995 [1974]), changing jobs (Bian, 1994, 1997) and getting good jobs (Marsden and Hurlbert, 1988; Lai, Lin and Leung, 1998; Erickson, 2001). However, should we expect personal contacts to work the same way in all kinds of labour markets? This seems a logical question, but the relative role and usefulness of job contacts within and between labour market contexts remain relatively unexplored in the literature.

Many researchers into the network theory of job searches argue that personal contacts, whether offering nuanced information (Wanous, 1980), facilitating newcomer socialization (Fernandez, Castilla and Moore, 2000) or providing timely influence (Bian, 1997), enable better job matches than non-network methods. Others like Granovetter (1973), Montgomery (1992), Burt (1992) and Lin (2001) posit that certain network characteristics such as weak ties, structural holes and high-status contacts can be more important than matching methods. I argue that while matching methods and network characteristics are important, labour market contexts influence the extent to which either is useful.

More specifically, using representative data from Singapore but drawing comparisons with information on the United States and other countries, I show that “who you know” does not always lead to better job outcomes, especially where recruitment and

promotion procedures are highly formal and bureaucratized. The heavy reliance on academic credentials for choosing the best candidates in Singapore’s state sector reflects a situation where educational and labour market hierarchies are tightly-linked and hence impermeable to informal influences such as networking.

Broadly, this paper contributes to our growing understanding of the effects of institutional contexts on the role and value of job contacts. It argues that cultural explanations do not suffice in explaining variations in the use and value of job contacts.

INSTITUTIONAL EXPLANATIONS

Rates of contact use vary by national context. In the United States, between 50% and 65% of Americans report using contacts (Granovetter, 1974; Lin, Ensel and Vaughn, 1981; Campbell and Marsden, 1990; Lai, Lin and Leung, 1998). Rates are noticeably lower elsewhere. In East Germany (under Communism), 40% found jobs through personal contacts (Völker and Flap, 2001). In the Netherlands, the percentage is between 35% and 50% depending on the period (see DeGraaf and Flap, 1988; Moerbeek et al., 1995). In Japan, the percentage is about 35% (Watanabe, 1987). In China, it about 45% (Bian, 1997), although another study found that only 23% of men and 14% of women used a contact when finding their first job (Lin and Bian, 1989).

Job contact effects on post-hire outcomes also differ between countries. Although studies indicate that high-status contacts consistently yield better post-hire outcomes (e.g. see Lin’s summary of studies, 2001:84), the sizes of these effects may vary according to which society is being studied. Some studies have found a positive effect of contact use on post-hire outcomes (e.g. Coverdill, 1998 in the United States concerning wages and Bian, 1994 in China concerning occupational change and non- state to state sector mobility), while others have found no or negative effects (e.g. Korennman and Turner, 1996; Lin, 1999; Mouw, 2003, all in the United States).

Variations in contact use and their effects within and between countries signal a need to explore their structural antecedents.

While laypersons and scholars alike may be tempted to rely on cultural explanations to account for national variations, cultural explanations could obscure the important role of institutional factors. Culture may be important for providing individuals with “routine scripts” and “lines of action” (Swidler, 1986:277), but culture often intersects with institutions to shape behaviour. Noting the role of job contacts in a variety of countries, Granovetter (1995) notes that while there may be somewhat more cultural emphasis on strong ties in countries such as China and Japan, most of the reasons for network differences seem to lie in institutional variations. Lin (1999) concurs, arguing that national differences in the use of job contacts are likely the result of institutional factors, for instance, the association between specific educational institutions and methods of job allocations and searches. Building on this argumentation, this paper examines how education and employment systems impact the role and payoffs of contact use in countries as diverse as Singapore and the United States.

Singapore is an excellent case study because it is located at one ideal-typical extreme of a distribution of meritocracy (Evans and Rauch, 1999). In their innovative paper, Evans and Rauch (1999) devised a “Weberianness scale” to measure the extent to which a group of 35 countries possess strong state bureaucracies characterized by meritocratic recruitment and predictable career ladders. The fact that Singapore was rated at the top of this scale makes it an ideal fieldsite for testing the relationship between bureaucratic labour market structures, job contacts, education and status attainment. Although Evans and Rauch (1999) did not include the United States in their study, Evans believes that the United States is on the whole less “Weberian” than Singapore (per. comm.).

VARIETIES OF CAPITALISM

My analysis draws upon a distinction in the varieties of capitalism literature (Hall and Soskice, 2001): “liberal market economies” (LMEs) and “coordinated market

88 economies” (CMEs). Briefly stated, LMEs and CMEs are ideal-type economies situated at the extreme ends of an array of nations. While multiple features distinguish LMEs and CMEs, one feature is the interrelationship between the supply (education) and demand (employment) sides of the labour market (Allmendinger, 1989).

In LMEs, the supply and demand sides of the labour market are “loosely-coupled”: that is, education systems in liberal economies send only weak signals to employers about the skills and qualifications of the labour pool. In CMEs, the supply and demand sides of the labour market tend to be “tightly-coupled” with education systems sending strong signals to employers about their potential employees. In the literature, the United States is often associated with LMEs, while countries like Norway and West Germany are more often associated with CMEs (Allmendinger, 1989; Mayer, 2005). Based on the distinction between loosely and tightly coupled, Singapore is more aptly described as a CME.

LMEs and CMEs may be further distinguished by standardization of educational provisions and the stratification of educational opportunities (Allmendinger, 1989; Mayer, 2005). In LMEs, schools have greater flexibility in the design and administration of their educational provisions. They have few prescribed national guidelines or standards. National examinations, particularly at the elementary and junior high school levels, are almost non-existent, and the idea of educational tracking at a young age is virtually unknown. Since students do not sit for national examinations, the signaling role of grades and certificates in LME labour markets is a less important issue.

Educational certificates are of relatively minor importance in LMEs as work lives by individual attempts to make good earnings (Mayer, 2005:36). While a university degree is qualitatively different from a high-school diploma, because of the large number and types of colleges and universities in LMEs, it is difficult, even with visible degree and grade differences, to judge between so many different types of graduates. The symbolic role of modern education compounds the problem -- as Dore (1976: ix) notes: “…not all

89 schooling is education… much of it is mere qualification-earning”. Given the uncertain meanings attached to degree, diplomas and grades in LMEs, employers may often rely on network mechanisms to select the best candidates, in addition to relying on formal qualifications.

CMEs are characterized by a standardized and examination-based school system. CMEs whether West Germany, Norway (Allmendinger, 1989), Japan (Dore, 1976; Rosenbaum et al., 1990), Hong Kong, Korea, Taiwan or Singapore (Schmidt, 2006), are united by the highly-significant role of qualifications for job allocation. The close relationship between “school” and “job” starts early in elementary school, when students are tracked into ability streams which set them up for certain kinds of employment (Cheung, 1994). Given that education is itself a rigorous sorting process, employers “can rely on information given by certificates and do not have to screen or train individuals entering the labour force” (Allmendinger, 1989:60).

To be clear, it is not that credentials are of little importance in LMEs. Standardized tests such as the SAT, GRE and GMAT have been an integral part of the North American tertiary education system, and doing well in them continues to be extremely important for gaining entry into prestigious universities. Furthermore, entry into professional careers requires specific forms of education, often in professional schools (DiMaggio and Powell, 1983). The difference between CMEs and LMEs is that the sorting process begins much earlier in the former (Turner, 1960). Furthermore, while LMEs may use a combination of credentials and networks to determine job hires, CMEs pay much more attention to credentials alone. In the Singapore CME, education alone makes for all kinds of great matches, particularly in highly-meritocratic jobs (MacDougall and Chew, 1976; Tan, 2004). The argument advanced in this paper is that in CME type labour markets where education and employment systems are tightly-coupled, personal contacts are generally ineffective. By contrast, in LME type labour markets where education and employment systems are loosely-coupled, personal contacts are more useful.

SINGAPORE CONTEXT

In addition to its CME categorization, Singapore has been called the “quintessential developmental state” (Castells, 1988:4). The most pressing objective of a developmental state is economic growth, even if at the expense of political freedoms (Kim, 1994). In the literature, the developmental state is often contrasted with the liberal market economies (LMEs) of Britain and the United States where the government’s role in the economy is more regulatory than interventionist (Wade, 1990; Woo-Cumings, 1999).

Between 1965 and 1984, Singapore saw the rise of an “administrative state”, whereby politics was removed from civil society and national decisions devolved to government bureaucrats (Chan, 1989). Because the administrative state is technocratic, its mode of leadership renewal is often informed by an elitist and meritocratic selection process based on academic achievement rather than personal charisma (Barr, 2006). In practice, the Singapore case is very similar to the French developmental state whose administrative elite is recruited from France’s grande ecoles . These grande ecoles lead to well-paid and prestigious positions within the civil service and state enterprises, thus reinforcing France’s reputation as a “Republic of Valedictorians” (Loriaux, 1999:240). As in France, the Singapore state is built upon a system of identifying and grooming scholars for high-level government work. The Singapore state is also much like ancient China’s Confucian Mandarinate, whereby examination stalwarts are sponsored into the highest positions within the state bureaucracy (Barr and Skrbis, 2008).

The developmental state draws its ideological power and legitimacy from its sterling economic performance and heavy reliance on human capital (Johnson, 1982; Castells, 1988). Without economic growth, the developmental state quickly loses its political legitimacy and must find a way to restore confidence among the electorate. The state’s answer to electoral expectations is, ironically, to intervene even more in industrial allocations (what jobs to do) and educational policy (what subjects to study). In the

Singapore developmental state, human capital development, technocratic planning and political stability are cited as fundamental engines of economic growth (Castells, 1988).

The eviction of Singapore from Malaysia in August 1965 (due primarily to Singapore’s persisting stand on meritocracy and its subsequent refusal to accede to Malaysia’s racial politics), allowed the ruling People’s Action Party (PAP) to play on public insecurities and propagate an ideology of survivalism (Chan, 1971; Tremewan, 1994). The lack of natural resources in the island city-state, coupled with its geographical realities (particularly its small size) enabled the Singapore state to generate a discourse underscoring the redemptive role of an important substitute: human capital.

Unlike other East Asian economies (e.g. Japan, South Korea and Taiwan) which built their post World War II economies on the strength of entrepreneurial ventures initiated by local capitalists (hence the rise of economic giants such as Toyota, Honda and Samsung), Singapore chose the path of MNC-led growth (Schuman, 2009). To stem the tide of growing unemployment, the state elites marketed Singapore as a low-cost manufacturing base for foreign capital (Castells, 1988). During the 1960s and 1970s, American and European companies were looking for offshore manufacturing bases for their electronics sector, and Singapore had by that time, an attractive mix of developed infrastructure, tax incentives, and educated labour (Castells, 1988; Tremewan, 1994).

Today, multi-national companies (MNCs) continue to be an important part of Singapore’s economic landscape, but competition has certainly intensified with MNCs seeking out cheaper locations (Ngiam, 2006). To remain competitive, Singapore has had to re-invent itself, i.e. upgrade its human capital and technological base while keeping wages in high-end industries relatively low. The latest direct foreign investments have been in the areas of pharmaceuticals and biotechnology -- human capital intensive spheres (Pereira, 2008).

Singapore’s powerful state sector has three important sets of institutions: the civil service; statutory boards; and state enterprises (otherwise known as government-linked companies or GLCs). The main criterion for entering the state sector is good academic performance (Neo and Chen, 2007). By enforcing meritocracy within the state bureaucracies, political elites can select the most talented individuals (Quah, 1998). To attract and keep the best talent, bureaucratic salaries in Singapore are about 10 percent higher than wages in comparable private sector positions (Evans, 1995). Although the state sector employs only about 20% of the workforce, its contribution to GDP is almost 45% (Castells, 1988).

Singapore’s rigorous academic tracking system extends into the military service that all 18-year-old Singaporean males undergo. Typically, those with excellent GCE ‘A’ level scores are assigned to scholar platoons for officer-cadet training (OCS) and are considered for prestigious government scholarships to top universities abroad. After their three to four year stints, these officer-cadets return to Singapore to serve their bond for their state sector employer (Barr, 2006). Depending on national needs, some are seconded to state enterprises (GLCs) where they are groomed for important roles mediating the link between state initiatives and free market.

Like the civil service, the GLCs are known to offer overseas scholarships to attract young talent and bind these young people for six to eight years (see Chan and Ng, 2000:295/6). As state enterprises, GLCs often have access to the civil service’s pool of talented elites. Indeed, some high-ranking civil servants are known to sit on the boards of GLCs, and a few are sequestered to them full time (Krause, 1989:443; Worthington, 2002). GLCs have great economic power. One Singapore study found that although GLCs “are no more or less liquidity-constrained in their investment decisions than their private sector counterparts”, they are “rewarded in financial markets with a premium of more than 20 percent” (RamÃrez and Tan, 2003:20).

The private sector tends to be less focused on credentials than the state sector. In Singapore, the private sector comprises two major groups: the multinational companies (MNCs), and the large but relatively powerless small business sector (or ‘SMEs’ standing for small and medium-sized enterprises). These SMEs value education, but they do not enforce it to the same exacting degree as the state sector. We may expect social networking to play a more active role in entering the SMEs (Tong and Yong, 2002), and there is anecdotal evidence that in Singapore’s high-end banking industry recruitment is based predominantly on old boy/girl networks.

Although Singapore contains three main ethnic groups: Chinese, Malay and Indian, Chinese predominate in the private sector arguably because during British colonial rule, they were assigned by the British to trade and commerce, with many working as coolies, shopkeepers and middlemen agents facilitating trade relations between the Europeans and locals (Visscher, 2007). Traditionally, then, Chinese have concentrated in sectors such as retail and wholesale, construction and light manufacturing, and banking. These industries tend to be network-based rather than human capital-based (Chan and Ng, 2000).

The three analytical frames I have adopted: 1) meritocracy and Weberianness, 2) CME versus LME and 3) the developmental state, while distinct ideas on their own, are interrelated in practice. Meritocracy creates a system whereby the best are allocated to the best jobs in the state sector. Elite civil servants are transformed into technocrats and economic agents whose mandate is to fulfill the economic goals of the developmental state. The growth of the economy through human capital development and other systematic and ‘Weberian’ means strengthen the citizenry’s belief that educational qualifications are the most important signal in labour markets (i.e. CME). When education and labour markets operate in meritocratic and hence predictable ways (and is accompanied by high economic growth), the political legitimacy of the state is enhanced.

PROPOSITIONS

According to one influential school of thought, institutions refer to the set of “constraints and rules” which exist to create order and reduce uncertainties in exchanges between social systems (North 1991:97). These constraints and rules make institutions predictable: over time, participants become familiar with the institution’s incentive structure and orient their behaviour accordingly.

A prevailing institutional rule of education-based meritocracies is that jobs are allocated based on ‘what you know’ rather than ‘who you know’. According to this rule, job allocation should depend on achieved criteria such as formal qualifications and accumulated skills rather than ascribed characteristics such as gender, ethnicity, family background, or social connections. In meritocratic markets, criteria other than human capital will interfere with the selection of the most competent workers (Reskin and McBrier, 2000). To the extent that developmentalism is sustained in a meritocracy, we should expect to see job seekers more reliant on educational resources than personal contacts.

Proposition 1: In highly-meritocratic societies where educational credentials are highly sought after by employers as evidence of future productivity, job seekers are less likely to use personal contacts.

As credentials are highly-valued in meritocratic society, we should expect to see well- educated job seekers relying on their hard-earned credentials. Meanwhile, individuals who lack credentials will have to rely on alternative strategies such as job contacts. This principle of substituting social capital for a lack of human capital is reported in studies of ethnicity and immigration where individuals from lower-status ethnic groups rely on personal contacts to enter ethnic economies (Light and Gold, 2000; Sanders, Nee and Sernau, 2002).

Proposition 2: In highly-meritocratic societies, highly-educated individuals are less likely than lower-educated individuals to rely on personal contacts during job search.

Assuming that well-educated job seekers are more likely to enter meritocratic jobs than lower-educated job seekers, and that meritocratic jobs are likely to value credentials over personal contacts, I hypothesize that well-educated job seekers are less likely than lower-educated job seekers to experience added returns from using job contacts.

Proposition 3: In highly-meritocratic societies, the well-educated are less likely than the lower-educated to experience added returns (i.e. earnings) from job contacts.

Individuals with sterling academic results are the preferred candidates in the state sector. Since coming to power in 1959, the former Prime Minister, Lee Kuan Yew had always pushed the meritocratic principle in his policies. In the words of Lee himself in a 1961 speech (in Quah 1998:111):

I am in favour of efficient service. The brighter chap goes up and I don’t care how many years he has been in or he hasn’t been in. If he’s the best man for the job, put him there.

While the meritocratic ideology came from Lee, its implementation was often entrusted to his Finance Minister, Dr Goh Keng Swee. Goh’s version of meritocracy was at times even more exacting than Lee’s. Holding a doctorate in Economics from the London School of Economics (LSE), Goh “placed a high premium on intellectual ability and academic brilliance, rather than experience… and as Goh had carte blanche to hire anyone from the list of government scholars given to him, he paved the careers of many young officers” (Neo and Chen, 2007:163). This “best man” policy was recently reiterated by current Prime Minister Lee Hsien Loong, in a conversation with Charlie Rose (reported 16 April 2010 in the Straits Times): “The whole of our system is founded on a basic concept of meritocracy. You are where you are because you are the best man for the job, and not because of your connections or your parents or your relatives.”

Based on Singapore’s strongly meritocratic state structure, we would expect the following two patterns:

Proposition 4a: Job contacts are less likely to facilitate entry into the meritocratic state sector.

Proposition 4b: Job contacts are less likely to pay off in the meritocratic job sector.

In addition, we would also expect job contacts to be less likely than formal mechanisms to facilitate entry into industries that emphasize formal credentials.

Proposition 5: Job contacts are less likely to be associated with entry into formal industries such as public administration and defence, health and social work and education.

High-status job contacts

A consistent finding is that high-status contacts create better post-hire outcomes for job- seekers (Lin, 2001), arguably because high-status contacts provide better access to resources and thus wield greater influence. Therefore, it is important to study the role of high-status contacts, in addition to contact use alone (Mouw, 2003). High-status contact use is a more targeted measure of social capital as it specifies the status of the job contact being mobilized.

I hypothesize that if a social system is highly meritocratic, then high-status contacts (even though they embody better resources) should not provide additional advantages. That is, the economic payoffs associated with using a high-status job contact should not surpass the economic payoffs associated with using a non-high-status contact. Proposition 6 will be stated as follows:

Proposition 6: In a highly-meritocratic society, high-status social capital will not lead to better earnings.

Proposition 7 is like Proposition 3. It asserts that well-educated job seekers are less likely than lower-educated job seekers to experience added returns from social capital. In highly-meritocratic societies, the payoffs to social capital should tend to be lower for people with educational advantages.

Proposition 7: Well-educated contact users are less likely to experience added returns from high-status contacts than less-educated contact users.

DATA AND METHOD

I analyze data from the 2005 Project Network Survey , using a sub-sample of 656 currently employed Singaporean adults aged between 25 and 55. The survey was designed to better understand the nature of personal communities in multiethnic Singapore. Like Fischer’s Northern Californian study (Fischer, 1982), the survey employed a range of 12 name generators to delineate the names, followed by questions about each network member and the nature of the ties. The exact wording of the questions was modified (after pre-tests) to suit the Singapore context. To ensure quality, the data were collected with the help of a highly reputable market research company, ACNielsen.

Following Granovetter’s (1974) study, the survey included a question about how respondents found their current jobs. As people often find their jobs through a combination of means (Montgomery, 1992), a multiple response question was called for. The options were the following: 1) I saw an advertisement in a newspaper (or other sources of media); 2) I found out through an employment agency; 3) I submitted an application; 4) Someone I didn’t know contacted me and said that I had been recommended; 5) I asked friend/person who told me about the job; 6) A friend/person who knew I was looking for a job contacted me; 7) A friend/person who didn’t know I was looking for a job contacted me; and 8) Others. Respondents who indicated options 5, 6 or 7 were assigned ‘1’ on the job contact variable, while the remaining respondents were assigned ‘0’.

Table 1 presents information about the sample. Most of the respondents are between 40 and 44 years of age (23.3%), although other age categories are represented as well. Males and females constitute 58.4% and 41.6% of the sample respectively; this uneven gender distribution is due to men’s greater participation in paid labour markets than women. As the numerically dominant ethnic group, Chinese make up 67.8% of the sample, while Malays and Indians make up 18.6% and 13.6% respectively. The sample distinguishes between three educational groups: 25.0% have ‘low’ levels of education (i.e. no formal education or some secondary education), 40.9% have ‘middle’ levels of education (i.e. completed secondary school, technical school or pre-university) and 34.2% have ‘high’ levels of education (i.e. polytechnic or university graduate). Of the respondents, 24.3% are employed in public sector jobs (comprising the civil service, statutory boards and GLCs) while 55.4% and 20.3% are employed in the small business sector (SMEs) and multinational companies (MNCs) respectively. 91% are fully employed, and 9% are employed part-time.

Of the 656 respondents, 233 were contact users (35.5%). This percentage of 35.5% is substantially lower than the percentages in the United States (50% to 65%), but closer to the percentages in Japan (35%), the Netherlands (35%-50%), East Germany (40%) and China (25%-45%). An earlier Singapore study conducted by Bian and Ang (1997:1002), found that 35% of their Singaporean respondents had used a personal contact to find a job: this is almost identical to the current study’s 35.5%.

Of all the contact users, 77.3% used an intimate tie (i.e. ‘close’, ‘quite close’ or ‘very close’) to obtain their current jobs. This concurs with findings in the literature, which suggest that job-seekers in predominantly Chinese societies tend to rely on strong ties during the job search (Bian, 1997; Bian and Ang, 1997). Among contact users, friends (57.6%) and kin (23.1%) were most likely to be relied upon, suggesting that strong-tie- bridges are important sources of job information.

Although Singapore is like China, a predominantly Chinese society where strong ties are important for job matching, the reasons for mobilizing strong ties are possibly different depending on the country. In China, strong ties are mobilized to get around bureaucratic structures of government and facilitate illegal job changes. In Singapore, strong ties are important because they aid the selection of reliable workers into private sector jobs (see Bian and Ang, 1997).

Outcome variables – Contact use and Earnings

The dependent variables are either contact use or earnings (per month) depending on the analysis. Contact use is dichotomous. Earnings are measured by the square root to the numeric codes representing each of 17 earning categories.

Focal independent variables

Depending on the hypothesis being tested, the focal independent variable is either: 1) used a job contact (vs. did not use a job contact) or 2) used a high-status job contact (vs. used a non-high-status job contact). In the latter, the respondent was asked to report whether the job contact had a: 1) much lower status than the respondent, 2) lower status than the respondent, 3) a bit lower status than the respondent, 4) same status as the respondent, 5) a bit higher status than the respondent, 6) higher status than the respondent or 7) much higher status than the respondent. I dichotomized the variable: respondents who indicated 5, 6 or 7 were considered to have used a high-status contact (1), while the rest are considered to have used a non-high-status contact (0).

The problem of contact use

One problem with studying contact use and post-hire outcomes is that one never really knows whether the contact affected the post-hire outcome or if another means of job search used in tandem with the contact was more important (Montgomery, 1992). One solution is to confine the analysis to the early stage – that is, study the sources of contact use without seeking to model the effects of contact use on post-hire outcomes.

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TABLE 1. DESCRIPTIVE STATISTICS OF SAMPLE OF SINGAPORE CITIZENS AND PERMANENT RESIDENTS (N = 656).

RESPONDENTS’ PERSONAL CHARACTERISTICS Age: 25-29 years 11.9% 30-34 years 16.2% 35-39 years 17.4% 40-44 years 23.3% 45-49 years 17.7% 50-55 years 13.6%

Gender: Male 58.4% Female 41.6%

Ethnicity: Chinese 67.8% Malay 18.6% Indian 13.6%

Employment status: Full-time 91.0% Part-time 9.0%

Education: ‘Low’ education 25.0% ( No formal education or some secondary ) ‘Middle’ education 40.9% (Completed secondary or technical or pre-university ) ‘High’ education 34.2% (Polytechnic, professional qualification, University )

Work sector: Private sector – Small business sector (SMEs) 55.4% Private sector – Multinational Companies (MNCs) 20.3% Public sector – Civil service, statutory boards and GLCs 24.3%

JOB SEEKING TIE CHARACTERISITCS: Proportion of job contact users 35.5%

Role relations of contact persons: Kin 23.1% Friends 57.6% Coworkers/supervisors 18.5% Neighbors .008%

Tie strength with contact persons: Very close 26.9% Quite close 26.9% Close 23.5% Not that close 21.0% Distant 1.7% Median tie strength ‘Close’

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Another less restricting solution is to measure the extent to which multiple search methods are used by job seekers (i.e. check the extent of multiple responses) and then decide whether to proceed with post-hire models. If the extent of multiple search methods is small, the researcher may justifiably proceed with the modeling. If the overlap in big, the researcher may refrain or proceed while stating the limitations.

In my case, the number of job seekers who reported using a combination of methods (formal and informal) was extremely small: 2 out of 656 respondents. Almost all respondents indicated either using a job contact (231) or some formal mechanism (407) (with only 2 indicating both and 16 indicating ‘others’), suggesting that technically, the problem of multiple search methods is not a serious one in this particular study.

But assuming that this figure is being underestimated due to factors such as respondents choosing to report in terms of their most primary search strategy instead of reporting multiple strategies (the question did permit multiple responses), then we need 1 other reasons for estimating post-hire models . Above all, we have to acknowledge the limitations and interpret the data with them in mind.

Controls

1 The problem of multiple search strategies notwithstanding, many scholars (e.g. Bian, 1994; Mortensen and Vishwanath, 1994; Fernandez and Weinberg, 1997; Coverdill, 1998; Fernandez, Castilla and Moore, 2000; Castilla, 2005; Antoninis, 2006; Loury, 2006; Behtoui, 2008; Stainback, 2008) have through the years, continued to estimate and report the impact of contact use on post-hire outcomes and publish their findings in top and reputable journals. Substantively, contact use reflects general properties which matter for status attainment: 1) contacts provide useful information that enable job seekers to self-select into jobs they expect to do well in, 2) contacts provide a smoother transition into the prospective firm (especially if the contact is from the firm) and 3) contacts are often willing to put in a good word on behalf of the job seeker. Each of these mechanisms may influence post-hire outcomes (such as earnings and tenure on the job) in substantial ways.

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The effect of the respondent’s education is represented by two dummy variables: ‘middle’ education and ‘high’ education, with ‘low’ education being the reference group (see Table 1 for the meaning of the categories). Age and age square are used as proxies for overall work experience. Gender, ethnicity and employment status are added as further controls, with male, Malay and full-time work being the reference groups respectively.

Interactions

I test a number of interaction effects:

a) [Job contact] x [Respondent has middle education]

b) [Job contact] x [Respondent has high education]

c) [Job contact] x [Respondent works in the state sector]

d) [High-status job contact] x [Respondent has middle education]

e) [High-status job contact] x [Respondent has high education]

The first two interaction terms (a, b) test Proposition 3, which predicts that payoffs to contact use are lower for highly-educated individuals. The fourth and fifth interaction terms (d, e) test Proposition 7, which predicts that payoffs to high-status job contacts are lower for highly-educated individuals. The third interaction term (c) tests Proposition 4, which predicts that payoffs to contact use are lower for individuals working in highly-meritocratic jobs (i.e. the state sector).

To test Proposition 2, I employ a binary logistic regression whereby I estimate the effects of education, ethnicity, gender and age on the odds of using a job contact. It is hypothesized that as education increases, the likelihood of contact use decreases. To test Proposition 5, I simply compare the proportion of job contact users across various industries. These industries include manufacturing, utilities, construction, wholesale

103 and retail trade, hotels and restaurants, transport, storage and communications, financial intermediation, public administration and defence, education and health and social work.

RESULTS

1) Low level of contact use in Singapore

Of the 656 currently employed respondents, 233 reported using job contacts. This percentage of 35.5% is substantially lower than the 50%-65% reported in North American studies, suggesting that on average, contact use is a much less prevalent job matching strategy in coordinated markets (CMEs) than in liberal markets (LMEs). National differences in contact use is interrelated, I argue, with the way in which education systems interface with employment systems in societies. In Singapore, educational credentials send strong signals to employers about a candidate’s ability to perform, while in the United States, these signals tend to be weaker and thus, are often supplemented by additional signals such as personal contacts (see Mayer, 2005:38).

Likewise, the lower rate of contact use in countries like Japan (35%), the Netherlands (35%-50%), East Germany (40%) and China (25%-45%) may be attributed to strong linkages between educational qualifications and job allocations in these CME-like societies (Allmendinger, 1989; Mayer, 2005). The range of contact use rates is notably wide in China. Some scholars believe that as China modernizes, contacts have become even more essential as bridges of institutional gaps (e.g. Bian, 2002). Other scholars (e.g. Guthrie, 2002; Hanser, 2002) believe that the strengthening of institutions in China has generally reduced contact use. A possible resolution for both these viewpoints is to say that while contacts may be of reduced importance in China’s modernizing sectors, they remain critically important in China’s less developed markets and job sectors.

2) Highly-educated individuals are less likely than lower-educated individuals to rely on job contacts

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Model 1 in Table 2 shows that highly-educated job seekers are less likely than middle or low-educated job seekers to use job contacts (- .746*** for ‘middle’ education and - 1.220*** for ‘high’ education). This inverse relationship remains significant at the .01 level when ethnicity, gender and age are controlled for (in model 3). Model 3 indicates that highly-educated respondents and middle-educated respondents are about four times (1/.244 = 4.10) and two times (1/.463 = 2.16) less likely than low-educated respondents to use job contacts respectively, suggesting that educational credentials reduce a job seeker’s need to rely on job contacts.

Model 2 indicates that Chinese are more likely than Malays (and Indians) to use job contacts (.435*). When ethnic differences in education are accounted for in model 3, the Chinese effect on job contacts becomes even stronger (.709**), implying that their high credentials suppress their use of job contacts. So the question becomes: if well-educated people usually do not use contacts (model 1), and Chinese lead in education, why is it that Chinese are still most likely to use contacts (e.g. .435* in model 2 and .709** in model 3)? While Chinese culture is one plausible explanation, another explanation, this time from an institutional viewpoint, would be Chinese’s active participation in the network-intensive spheres of the Singapore economy.

Notice that when the effects of private sector firms (namely SMEs and MNCs) are added in model 4, the impact of Chinese decreases from .709** (in model 3) to .618* (in model 4) suggesting firstly that the active participation in private sector jobs by Chinese is a substantial source of their high contact use. Furthermore, since the effect of Chinese on contact use does not disappear but persists in model 4, we may argue that cultural factors account for their active use of job contacts. However, such an argument must remain tentative, since the models do not yet incorporate all relevant institutional factors. In sum, the pervasive use of job contacts among Chinese is probably due to some meaningful (albeit tentative) combination of cultural and institutional factors. More research needs to be done, preferably between different kinds of Chinese societies, to ascertain the actual size of the alleged cultural effect.

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3) Job contacts are less likely to pay off for the well-educated.

Table 3 shows that job contacts are negatively associated with earnings (- .261***, model 1). When controls for respondents’ education, gender, age and ethnicity are added (in model 2), the negative relationship remains significant at the .01 level (- .084**), suggesting that job contacts are associated with downward mobility, net of other factors. This downward effect could be interpreted to mean that job contacts are not so much a strategy for getting ahead, as they are a substitute for lack of formal resources.

TABLE 2. BINARY LOGISTIC REGRESSION ESTIMATING THE EFFECT OF EDUCATION ON CONTACT USE

Predictors Model 1 Model 2 Model 3 Model 4

Middle education - .746*** - .770*** - .654** (.474) (.463) (.520) High education -1.220*** -1.409*** - 1.217*** (.295) (.244) (.296) Chinese .435* .709** .618* (1.545) (2.031) (1.855) Indian - .034 .150 .246 (.966) (1.162) (1.278) Female - .301 - .223 - .189 (.740) (.800) (.828) Age .078 - .046 - .021 (1.081) (.955) (.979) Small business .915*** sector (SMEs) (2.496) Multinational .789** companies (MNCs) (2.201)

Intercept .098 - 1.210 .008 - .904 N 656 656 656 656 Degrees of freedom 2 4 6 8 Chi-square 32.166*** 12.461* 46.915*** 62.937***

NOTE. – Odds ratio of the response reported in parentheses OMITTED CATEGORIES. - Low education, Malay, Male, state sector. *P < .05. ** P < .01. *** P < .001 (two-tailed tests). -2LL intercept is 853.582

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The negative interaction effect, [(Job contact) x (R has high education), - .163*] in model 3 supports the proposition that well-educated job seekers tend to gain less from job contacts than less-educated job seekers (Proposition 2). For the well-educated, job contacts are a rather useless strategy for getting ahead.

If job contacts tend to be relatively useless for the well-educated, why do some university graduates still use them? A possible explanation is that employers may choose to evaluate their job applicants on multiple dimensions of education: for example, level of education (i.e. years of schooling) and quality of education (e.g. reputation of applicants’ university and grades). A pool of applicants may all be university graduates, but particularly in labour markets that seek talented candidates, excellent grades and reputable universities are distinguishing factors. In Singapore, a good university degree (e.g. first or second-upper class honours from a good university) is a highly valuable asset. University graduates with poorer grades often experience difficulties getting the best jobs, despite being well-educated (in terms of number of years) (see MacDougall and Chew, 1976).

The absence of significant ethnic effects on earnings (in models 2 and 3 of Table 3) is attributed to education effects already being accounted for. Indeed, educational inequalities between Chinese, Malays and Indians are a major source of earning differences between Singapore’s ethnic groups. The inequality dynamic of gender is in comparison different from ethnicity. As women are as likely as men to be well- educated, gender differences in earnings (models 2 and 3) may be attributed to factors other than education, such as persisting gender discrimination in paid work. In Singapore’s state sector, men are paid more than women, net of education. The state rationalizes the gender wage gap by evoking men’s later entry into paid work due to national (military) service.

4) Job contacts are less likely to pay off in meritocratic job sectors (i.e. the state sector)

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As credentials are especially important in Singapore’s state sector, it is not surprising that its employees are generally more highly-educated than employees in the private sector (6.96 vs. 6.01, t-test, .95*** in Table 4). Net of education, state sector jobs tend to pay higher than private sector jobs (.088* in Table 4): this corroborates Evans’ (1995) findings that bureaucratic salaries in Singapore are 10% higher than wages in comparable private sector jobs. Because of attractive salaries, state sector jobs are often target destinations for new university graduates, especially the high performers. The data show that state sector employees are significantly less likely than private sector employees to rely on job contacts (.18 vs. .43, Table 4), thus supporting proposition 4a.

The negative interaction effect in model 3 of Table 5a [(Job contact) x (R works in state sector), - .153 †] constitutes evidence at the .10 level that job contacts are not likely to be as useful in the state sector as in the private sector. This attenuating effect becomes more obvious when we make a further distinction between private sector jobs, namely: ‘small business sector (SMEs)’ and ‘multi-national companies (MNCs)’. The new reference category would be ‘small business sector (SMEs)’ (Table 5b) instead of the more general ‘private sector’ (Table 5a). With this distinction, the interaction term [(Job contact) x (R works in a state sector job), - .169* in Table 5b] registers a higher level of significance (p < .05), granting stronger support to proposition 4b.

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TABLE 3. OLS REGRESSION ESTIMATING THE EFFECT OF CONTACT USE ON EARNINGS

Predictors Model 1 Model 2 Model 3

Focal independent variable: Job contact - .261*** - .084** .009 (.045) (.033) (.061)

Control variables: Middle education .369*** .424*** (.040) (.055) High education .941*** 1.010*** (.045) (.057) Female - .204*** - .206*** (.031) (.031) Age .368*** .372*** (.071) (.071) Age square - .027*** - .028*** (.006) (.006) Chinese .036 .031 (.041) (.041) Indian .027 .026 (.055) (.055) Part time employment - .463*** - .463*** (.055) (.055)

Interactions: (Job contact) x (R has middle - .106 education) (.079) (Job contact) x (R has high education) - .163* (.085)

Intercept 2.508 .926 .870 R-square .0492*** .5393*** .5420*** Degrees of freedom 1 9 11 N 656 656 656

OMITTED CATEGORIES. – Low education, Malay, Male, Full-time employment. *P < .05. ** P < .01. *** P < .001 (two-tailed tests). Standard error in parentheses

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TABLE 4. JOB SECTOR DIFFERENCES IN EDUCATION, EARNINGS AND PROPORTION OF JOB CONTACT USERS # of Mean Proportion Difference in mean Job sector respondents education of job earnings between level contact public and private users job sectors when effect of education is controlled Public sector (1) 159 6.96 .18 Private sector† (2) 495 6.01 .43 Total or difference 654 .95*** - .24*** .088* (1) – (2)

INDUSTRIES Public Administration & 15.8 Defense Education 19.6 Health & Social Work 24.3 Electricity, Gas & Water 27.8 Transport, Storage & 29.5 Communication Financial Intermediation 33.3 Manufacturing 36.6 Real estate, Renting & 39.1 Business Wholesale & Retail Trade 50.7 Hotel & Restaurants 55.9 Construction 61.4 *P < .05. ** P < .01. *** P < .001 (two-tailed tests). † ‘Private sector’ includes both the small business sector (SME) and the multinational companies (MNC) sector

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TABLE 5a. OLS REGRESSION ESTIMATING THE EFFECT OF CONTACT USE ON EARNINGS BY JOB SECTOR

Predictors Model 1 Model 2 Model 3

Focal independent variable: Job contact - .258*** - .073* - .048 (.045) (.033) (.036)

Control variables: Middle education .358*** .357*** (.040) (.040) High education .925*** .924*** (.046) (.046) Age .368*** .359*** (.071) (.071) Age square - .027*** - .027*** (.006) (.006) Female - .208*** - .208*** (.031) (.031) Chinese .046 .040 (.042) (.042) Indian .023 .023 (.055) (.055) Part time employment - .454*** - .450*** (.055) (.055) State sector (civil service, statutory .076* .109** boards, GLCs) (.037) (.042)

Interaction: (Job contact) x (R works in state - .153 † sector job) (.088)

Intercept 2.508 .915 .932 R-square .0482*** .5403*** .5425*** Degrees of freedom 1 10 11 N 654 654 654

OMITTED CATEGORIES. - Low education, Malay, Male, Private sector, Full time employment. †P < .10. *P < .05. ** P < .01. *** P < .001 (two-tailed tests). Standard error in parentheses

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TABLE 5b. OLS REGRESSION ESTIMATING THE EFFECT OF CONTACT USE ON EARNINGS BY JOB SECTOR

Predictors Model 1 Model 2 Model 3

Focal independent variable: Job contact - .258*** - .068* - .041 (.045) (.033) (.041)

Control variables: Middle education .351*** .350*** (.040) (.040) High education .898*** .895*** (.046) (.046) Age .352*** .342*** (.070) (.070) Age square - .026*** - .025*** (.006) (.006) Female - .210*** - .210*** (.031) (.031) Chinese .049 .043 (.041) (.041) Indian .018 .017 (.054) (.054) Part time employment - .443*** - .438*** (.055) (.055) State sector jobs (civil service, .126*** .164*** statutory boards, GLCs) (.039) (.044) Multinational Company (MNC) .161*** .164*** (.040) (.050)

Interactions: (Job contact) x (R works in state sector - .169* job) (.089) (Job contact) x (R works in MNC) .00089 (.081)

Intercept 2.508 .920 .939 R-square .0482*** .5518*** .5545*** Degrees of freedom 1 11 13 N 654 654 654

OMITTED CATEGORIES. - Low education, Malay, Male, small business sector (SME), Full time employment. *P < .05. ** P < .01. *** P < .001 (two-tailed tests) Standard error in parentheses

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5) Job contacts are less likely to be associated with formal industries

Table 4 and Figure 1 support the hypothesis that job contacts are less likely to be associated with entry into formal industries such as public administration and defence, health and social work and education (Proposition 5).

Based on post-hoc one-way ANOVA tests, the industries being examined can be divided into three distinguishable clusters: generally, jobs in public administration and defence, education and health and social work tend to go with the lowest levels of contact use. Jobs in electricity, gas and water, financial intermediation, manufacturing, real estate, renting and business and transport, storage and communication tend to go with middle levels of contact use, and jobs in wholesale and retail trade, hotels and restaurants and construction tend to go with the highest levels of contact use. In sum, the more formal the industry, the less prevalent the use of job contacts.

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6) High-status job contacts do not result in higher earnings for contact users

Model 1 in Table 6 reports no significant relationship between high-status job contacts and earnings (- .029, ns). With relevant controls added in model 2, this non-significant effect persists (- .064, ns in model 2), suggesting that high-status job contacts do little to facilitate status attainment (Proposition 6). It appears, despite strong evidence of significant post-hire benefits associated with high-status contacts in many contemporary labour markets (see summary table in Lin, 2001:84), Singapore seems to 2 be make for an exception, at least in this particular study .

7) Well-educated contact users are less likely to experience added returns from high-status contacts than less-educated contact users

Model 3 in Table 6 tests the interaction between respondents’ level of education and the status of their job contacts relative to their own. The negative interaction effect, [(Contact has higher status than respondent) x (R has high education) - .293*], suggests that well-educated contact users are less likely than lower-educated contact users to experience added returns from using high-status job contacts (Proposition 7). This reinforces the point that those with already good credentials may often find social capital a less valuable route of status advancement.

2 Studying the United States, Mouw (2003) argues that high-status contacts relate spuriously with post-hire outcomes, and that any positive relationship is actually the result of homophilous friendship patterns. Given this endogeneity problem, Mouw suggest using other measures of social capital to measure and verify the positive relationship between social capital and post- hire outcomes. Furthermore, some scholars may choose to argue that the Singapore case is in fact no different from the American case. At this point, more research is required in the area of comparisons. But Mouw’s arguments notwithstanding, the overwhelming consensus in the literature is that high-status contacts do indeed make a substantial difference to post-hire outcomes in the United States and other countries (see the many studies reviewed in Lin (2001:83-87).

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TABLE 6. OLS REGRESSION ESTIMATING THE EFFECT OF HIGH-STATUS JOB CONTACT ON EARNINGS BY RESPONDENT’S EDUCATION

Predictors Model 1 Model 2 Model 3

Job contact is of higher status than - .029 - .064 .032 respondent (.070) (.050) (.085)

Respondent’s characteristics: Middle education .295*** .310*** (.056) (.069) High education .808*** .910*** (.070) (.082) Age .325** .322** (.114) (.113) Age square - .026* - .025* (.010) (.010) Female - .240*** - .238*** (.051) (.051) Chinese .025 .034 (.071) (.071) Indian .002 .017 (.097) (.097) Part time employment - .461*** - .467*** (.071) (.071)

Interactions: (Job contact has higher status than - .060 R) x (R has middle education) (.115) (Job contact has higher status than - .293* R) x (R has high education) (.131)

Intercept 2.264 1.140 1.120 R-square .0007 .5259*** .5372*** Degrees of freedom 1 9 11 N 237 237 237

OMITTED CATEGORIES. - Contact is of same or lower status than the respondent, Respondent has low education, Malay, Male, Part time employment *P < .05. ** P < .01. *** P < .001 (two-tailed tests). Standard error in parentheses

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DISCUSSION

I have drawn upon a distinction popularly used in the varieties of capitalism literature: ‘liberal market economies’ (LMEs) and ‘coordinated market economies’ (CMEs) (Hall and Sockice, 2001). Each shows a unique relationship between the education and labour sides of the labour market (Allmendinger, 1989). My results have suggested that in labour markets that stress the tight bureaucratic link between educational signals and labour markets, personal contacts are less prevalent and effective in job searches, especially among the well-educated and those working in the highly-meritocratic state sector.

While Singapore is a broadly meritocratic society and may have a strong meritocratic system in government, the extent of this meritocracy is less pervasive in the private sector. But this may soon change: using its political and economic clout, the Singapore state is pressuring private sector firms to emulate the meritocratic practices of government sector jobs. Indeed, the government has recently (in 2007) set up a council called the Tripartite Alliance for Fair Employment Practices (or TAFEP) , strongly encouraging employers to sign an “Employers’ Pledge” against discrimination in hiring. To date, 1000 private sector companies have signed and the numbers are growing.

In state sector jobs, the link between qualifications and earnings at entry level is clear and transparent. Recently, in the Ministry of Home Affairs, first-class graduates got a starting salary of $3,494; second-class (upper) honours graduates received $3,310; basic degree holders $3,310, and so on. With such standardization in place, there is little room for job contacts to influence remuneration outcomes. To be sure, salaries are adjusted after a few years; once the person is in the job and he/she is assessed on current performance. But the base-pay remains a function of formal qualifications.

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This is not to say that credentials are only important among Singaporeans or that only Singaporean employers consider them worthy. The growth of tertiary education around the world reflects the increasing importance of formal qualifications, even if its role is often symbolic and not always matched by real increases in productivity (Dore, 1976; Collins, 1979).

In Singapore, the symbolic power of credentials (assumed to be indicative of skills) is most palpable in the meritocratic state sector where there is ideological pressure to reward university graduates with good wages, despite weak increases in productivity. The allocation of wages is as much an economic process as it is an exercise in political/legitimacy-building. Indeed, it has been argued that Singapore’s university graduates are often over-qualified but under-skilled for their jobs (Appold, 2005).

Dore’s “credentialism” (1976) is probably stronger in Singapore than in the United States. Comparing Singapore and America, the former minister of education (of Singapore), Tharman Shanmugaratnam, said:

We both have meritocracies. Yours is a talent meritocracy, ours is an exam meritocracy. We know how to train people to take exams. You know how to use people’s talents to the fullest. Both are important, but there are some parts of the intellect that we are not able to test well – like creativity, curiosity, a sense of adventure, ambition. Most of all, America has a culture of learning that challenges conventional wisdom, even if it means challenging authority. These are the areas where Singapore must learn from America. (Zakaria, 2008:193-194)

In the North American context, talent is often elicited through a combination of credentials and networks; in fact, the two are often perceived as being inextricably bound together (see Coleman, 1988 or Erickson, 2001). In Singapore, talent is typically elicited through national examinations. Rodan (1996:24) notes:

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The pattern of increased educational attainment in Singapore is often compounded by the exceptional importance on credentials in ‘meritocratic’ Singapore… there is probably no other place in the world where formal qualifications represent as much economic or social capital.

This invites the question: what makes it so difficult to re-invent, change or move away from an exam-based meritocracy? One reason is that institutional structures are notoriously difficult to change (see Meyer and Rowen, 1977 and Hannan and Freeman, 1984 on organizational inertia, myth and ceremony). Power holders have a vested interest in reproducing their advantages, and education seems an expedient way to do it. As class factors (namely family background) are strong predictors of educational resources, children from wealthier families inadvertently get a head start (Bowles and Gintis, 1976). Indeed, meritocracy supplies the wealthy with a discourse which attributes personal success to meritocratic attributes such as effort and ability rather more structurally, initial class standing (Young, 1958).

In an exam-based meritocracy, education contributes indirectly to political stability by serving as the only (in principle) legitimate means of upward mobility. The motif of meritocracy generates the often unquestioned belief that individuals from humble backgrounds are as likely as individuals from privileged backgrounds to succeed if they are willing to work hard. Meritocracy upholds the myth of equal educational opportunities for all, and conceals the fact that kindergartens and elementary schools continue to vary greatly in quality. The logical end of a meritocracy is an elitist system whereby class privileges are reproduced through education, even as schools continue to be at least, partly, social levellers of inequality (Bowles and Gintis, 1976).

In Singapore, education is a means for the Chinese majority to maintain their political hegemony and economic dominance in relation to the other ethnic groups (Rahim, 1998). As the most highly-educated ethnic group in Singapore, the Chinese have a vested interest in upholding education as the most important route of status

118 advancement. Through education, they (especially English-educated Chinese) get to maintain their control over the powerful state and MNC sectors. Chinese-educated Chinese on the other hand, rely not on education, but on their networks to hoard opportunities within the small business sector. Either way, Chinese have secured for themselves -- either through education or networks – lucrative and stable positions within both state and non-state sectors.

Of course, one could argue that with only one country, it is hard to make an argument about national differences, and that we need data for other liberal and coordinated economies to be sure that the Singapore results are not due to something else like culture. This is one limitation of the study that further comparative work on national economies could seek to rectify.

CONCLUSION

Granovetter (1974) found that in the United States, more than half of his respondents used a personal contact to find a job. By contrast, this study shows that only a third of Singapore respondents used a contact. Why the difference? In his Afterword , Granovetter (1995:160) posits that “there do not seem to be sharp variations by country in what proportion of people find jobs through contacts, but institutional variations do lead to differences in the detailed process.” Based on my findings, I would disagree with the former part of his argument and agree with the latter – institutional variations do matter.

Cultural differences cannot fully explain the role of personal contacts in different kinds of job sectors and economies, and institutional involvement should also be considered. Several studies have pointed to the contingent nature of job contacts on status attainment (e.g. Granovetter, 1995; Burt, 1997; Guthrie, 2002; Lin, 1999), but the question of mechanisms needs further exploration. Evoking a “varieties of capitalism” framework, I have argued that variations in contact use and payoffs may be explained

119 by variations in the manner with which education and labour market systems are interrelated in different types of economies and job sectors.

While several LME-based studies show that high-status contacts lead predictably to status attainment (Marsden and Hurlbert, 1988; Lai, Lin and Leung, 1998; Lin, 2001), my study suggests that such effects do not necessarily apply to labour market institutions which rely heavily on academic credentials for job matching. Although individuals are free to choose the kinds of search methods they think relevant, contextual factors play a critical role influencing the usefulness of those strategies. My contention is that in order to better understand the role and value of job contacts one must consider the role of institutions, namely the different ways in which education and employment systems interrelate with each other within and between national economies.

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Chapter 5 (Paper 3) The Invisible Hand of Social Capital

This paper underscores the importance of institutional factors affecting the role and value of social capital in labour markets. Distinguishing between two broad categories of social capital: ‘accessed’ and ‘mobilized’ social capital, I ask: how do meritocratic constraints in labour markets affect the role and value of different kinds of embedded social capital? Using representative survey data from Singapore, I show that 1) social capital continues to be important even in highly-meritocratic jobs, and 2) that social capital works primarily through the invisible hand of ‘accessed’ rather than the visible hand of ‘mobilized’ in contexts of meritocracy.

INTRODUCTION

This paper aims to further our understanding concerning the impact of institutional contexts on the role and value of social capital. The contexts that I am concerned about are those characterizing meritocracies: that form of society that focuses heavily on formal credentials and that seeks to reward people according to their efforts, abilities and achievements rather than their ascribed characteristics such as gender, ethnicity, age, or social networks (Young, 1958; Goldthorpe and Jackson, 2008).

While there are many approximately meritocratic societies in the world today, a most notable extreme case is Singapore (Evans and Rauch, 1999). In their study of a group of some 35 countries (including countries such as Canada, Japan, Taiwan, South Korea, but not the United States), Evans and Rauch (1999), found that Singapore was the most “Weberian” among them: that is, Singapore had registered the highest score for having a highly formal state bureaucracy, for emphasizing meritocratic recruitment in state jobs and for having career paths that are transparent and predictable.

The meritocratic system of Singapore provides an excellent opportunity for asking some pertinent research questions: 1) how do meritocratic constraints influence the role and value of social capital in labour markets? 2) does the heavy emphasis on formal credentials in a meritocracy mean that social capital is consigned to play a marginal

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role? And 3) assuming that personal contacts are perceived as unethical in the context of meritocratic jobs, may we expect social capital to work in embedded ways?

ISSUES

Need to consider the role of contextual factors on social capital

Having social capital means having access to resources as a result of knowing influential people who have those resources (Lin, 2001). In the literature, discussions of social capital are often couched in a vocabulary of ‘investments’. The theoretical assumption is that people are motivated by expressive and instrumental needs that propel them to form (or ‘invest’) in interactions with others to gain resources such as wealth and reputation (Lin, 2001:184).

Such an instrumental viewpoint however tends to over-privilege the role of people’s choices over that of their environments. Indeed, an emphasis on choice arguably bestows too much power on individuals’ social networking abilities and skills, while downplaying the fact that labour market conditions profoundly affect the extent to which those networking abilities and skills are utilized and/or pay off. This paper underscores that it is important to consider the influential role of macro-institutional structures and constraints (such as the highly-meritocratic nature of some labour markets) on social capital, even as people seek to optimize their networks as social capitalists (Hsung, Lin and Breiger, 2009).

Comparing the United States, Taiwan and China, a recent study (by Son, 2008) found that macro-institutional constraints substantially affect the role and value of social capital in different kinds of societies and labour markets. The study had noted for example that mainland Chinese and Taiwanese Chinese were significantly less likely than North Americans to activate social capital during job seeking. One explanation being offered was the greater reliance on academic credentials in Confucian societies,

130 which results in job contact use becoming suppressed. Citing the case of South Korea (conjectured to be similar to China and Taiwan), Son (2008) recounts that it is common to see notices in government offices inscribed with following words: “Do not ask for favours through connections.” The South Korean state often perceives particularistic mechanisms such as school ties, regional ties and blood ties as signalling corruption.

In North America, by contrast, social networks are more actively utilized by job seekers and less likely to be saddled with negative connotations. In fact, networks are often perceived by North American job seekers and employers as necessary for facilitating the best kinds of job matches (Fernandez, Castilla and Moore, 2000; Erickson, 2001; Bolles, 2009). National variations in the use and meaning of job networks suggest that social contexts are important sources of the variations in networking practices, and that more research should be allocated to better understanding the macro-micro link between institutional constraints and networks (Hsung, Lin and Breiger, 2009).

More to social capital than job contacts alone

In earlier years, social capital research had focused quite predominantly on the impact of “job contacts” on individuals’ labour market outcomes. Job contacts were established as being important for helping people get jobs as well as enhance their occupational status (e.g. Granovetter, 1974; Marsden and Hurlbert, 1988; see Lin, 2001 for a review of many such studies). However, over time, with the invention of data collection methods such as the position generator (which allowed researchers to measure respondents’ access to people from diverse occupational locations within the social structure), it became clear that the conscious mobilization of job contacts was only one very specific aspect of networking, and that broader forms of social capital (namely accessed social capital), were important for job success as well (Lin, 2001; Lin and Ao, 2008).

In practice, job contacts represent only a slice or subset of the total social capital captured by research and are therefore an inadequate representation of the total potential of a person’s network (Lai, Lin and Leung, 1998; Lin and Ao, 2008). Whereas

131 mobilized social capital (i.e. job contacts) refers to the social ties and resources that are consciously activated in a specific event such as a job search (Granovetter, 1974; Lin, Ensel and Vaughn, 1981), accessed social capital refers to the entire capacity of a person’s network (Lin and Ao, 2008). Certainly, we need more research concerning how accessed and mobilized social capital operate in tandem -- as analytically distinct and yet integrated (Lin, 2001).

The distinction between accessed and mobilized reflects the dual way in which individuals relate with social capital. On one hand, people are social networkers who seek through job contacts for example, to optimize their job success (Lin, 2001). But on another hand, people are also social networked: that is, they are embedded within networks of social relations which they do not consciously activate, but which they benefit from in indirect ways (Granovetter, 1985; Small, 2009).

The resources accrued from accessed social capital may often be unanticipated, since such social capital is, by definition, not consciously activated (Small, 2009). This paper underscores the need to examine the unanticipated consequences of networks and argues that focusing on job contacts alone is not sufficient for measuring the impact of social capital and job success. Interestingly, while most studies have examined mobilized or accessed social capital on separate occasions, few have analyzed both under the rubric of a single study. And yet to do so constitutes a highly urgent research task (Lin and Ao, 2008). As accessed and mobilized social capital form distinct but integrated parts of personal networks, they should be analyzed in tandem, with a view to understanding their combined role in labour markets (Lin and Ao, 2008).

The substance of accessed social capital

According to Lin and Ao (2008), accessed social capital may often take the form of “routine job information”: this is the information that arises from encounters and conversations that “flow casually in a fragmented way and without explicit expectations” (Bearman and Parigi, 2004 cited in Lin and Ao, 2008). Here, the receiver

132 does not deliberately seek out such information or social resources but stumbles across it in the course of everyday life.

But there is more to accessed social capital than routine job information. Indeed, accessed social capital may include any kind of network-induced information and resources that potentially affects status attainment. These include:

1) Network-induced cultural capital : The acquisition of cultural capital is a highly social process. Families, for example, play an important role transmitting distinguished patterns of speech, etiquette and comportment to the next generation (Bourdieu, 1984). The persistence of legacy admissions in many elite schools in the contemporary world serves as an excellent example of how privileged resources, cultural capital and influential networks may often help privileged members of society hoard opportunities (Bowles and Gintis, 1976). So people may not have actually mobilized a job contact during the job search, but because of their embeddedness within advantageous family and friendship networks, get to acquire a repertoire of cultural and human capital which places them in good stead to experience job success.

2) Having good connections may often be a job credential in itself: Employers sometimes prefer candidates who possess a rich repertoire of networks, especially for managerial jobs (Erickson, 2001). Having a rich network is a reflection of several things which employers find attractive. First, a well-connected person usually has good interpersonal skills (if not he/she would not be well-connected in the first place) (Coser, 1975). Second, a well-connected person is an asset to a company because his/her networks may help him/her to contribute to its bottom-line, for example procure clients for the company (Erickson, 2001). Third, a well-connected person is likely to have a good social support system, and this makes him/her a physically and mentally healthy person (Pescosolido, 1992).

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Such a person is likely to be a productive worker and not burden the company with health claims!

3) Good networks lead to good ideas: Personal networks are sources of good ideas, especially if they consist of weak ties. Weak ties are important because they link people to social milieus which are less familiar and therefore novel and value- adding (Granovetter, 1973). In practice, the acquisition of good ideas is not just about delving into the books (although a human capital approach would tend to privilege such an argument), but the outcome of being embedded in networks that facilitate the exchange of bright ideas (Burt, 2004). Good ideas produce innovative workers who can contribute directly to the improvement of a company. Erickson’s research (1996) indicates that people with diverse networks often have a diverse repertoire of knowledge.

In an earlier paper (Chua, 2010), I demonstrated that job contacts were: 1) seldom utilized to enter meritocratic jobs, 2) associated with lower earnings, and 3) associated with lower increments in earnings, especially in meritocratic jobs: all these support the idea that meritocratic constraints tended to suppress the role and value of social networks. But this cannot be the end of the story as I had only examined job contacts, which is the visible hand of social capital. More theorization is needed concerning the invisible hand of social capital.

On why the invisible hand of social capital should be especially important in meritocracies

Meritocracy is a social system that seeks to reward people on the basis of merit: often- time “educational” merit (Goldthorpe and Jackson, 2008). In Singapore as with many other countries (particularly countries in East Asia), formal credentials are emphasized and deployed rigorously as a means of allocating people to the best jobs. In fact, to select workers based on any other means, such as networks, would imply some kind of corruption and therefore according to the rhetoric of meritocracy, illegitimate.

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The puzzle in this paper is essentially this: if the active mobilization of social capital is in the meritocracy saddled with such negative connotations as illegitimate, then what exactly is the role and value of social capital in such societies? Surely, networks continue to matter, but how so? How do meritocratic structures and constraints impact the way embedded forms of social capital interface with status attainment?

The thesis which I seek to advance is that in meritocratic jobs, social capital tends to operate in embedded ways. In a meritocracy, overt ways of social capital utilization such as mobilizing a job contact will generally be unpopular, especially in the most meritocratic of labour markets. Instead, embedded and diffuse network mechanisms will be more important and leveraging in those meritocratic labour markets.

Overall, this paper demonstrates the following:

1) Social capital continues to be an important predictor of job success, even in meritocratic jobs.

2) The primary way in which social capital facilitates job success in meritocratic jobs is accessed of social capital (i.e. the invisible hand of social capital) rather than mobilized social capital (i.e. the visible hand of social capital).

3) The more meritocratic the labour market, the more pronounced the role and value of accessed social capital relative to mobilized social capital.

I argue that the lesser importance of job contacts in meritocratic labour markets is not a sign that social capital is altogether unimportant. There are broader aspects of social capital that contribute to status attainment, even if job contacts do not.

SINGAPORE CONTEXT

The separation of Singapore from Malaysia in August 1965 (after just twenty three months of political merger) was due primarily to the issue of meritocracy. The

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Malaysian Prime Minister, Tunku Abdul Rahman and Singapore’s Prime Minister, Lee Kuan Yew were divided over how exactly to allocate the resources of a newly-formed Malaysia. Whereas Lee had pushed strongly for a society based on multiculturalism: that is, the equal treatment of ethnic groups (Hill and Lian, 1995:93), such an approach was at odds with Malaysia’s Malay-first (or ‘Bumiputra’) policy. The Malaysian Tunku wanted a Malay-centered society with privileges going first to Malays as natives of the land (Lee, 1998). The incompatibility of viewpoints and other political differences sparked serious ethnic riots in 1964, which led eventually to Singapore being thrown out of Malaysia a year later. Lee’s intransigent stand on meritocracy may be attributed partly to demographic factors: as about 75% of Singaporeans are Chinese, acceding to a ‘Malay-first-policy’ would have reinforced Singapore’s position of socio-economic disadvantage relative to their Malay neighbours, and why should Singapore, as a predominant Chinese state, want that?

The separation, it appears, had served only to strengthen Singapore’s determination to bring her meritocratic beliefs to an even higher level: that is, to move meritocracy beyond the realm of ideas, into the realm of durable institutions reflected thus in its politics, education, economy, and culture (Tan, 2008). Today, meritocracy pervades Singapore society and is used aggressively in the administration of its economic, political and social structures. The highly rationalized state sector, nicknamed “Singapore Inc.” (Economist, 2002), is the most powerful promoter of this meritocracy.

While the state is not the only organization in society, its influential presence exerts pressure on the other labour markets to conform to its meritocratic practices (DiMaggio and Powell, 1983). No discussion of Singapore is complete without considering the very influential role of this state apparatus (Yao, 2007). Ezra Vogel notes that “what is unusual in Singapore is not the prominence of meritocratic administrators, but the fact that this meritocracy extends upward to include virtually all political leaders” (cited in Quah, 1998:111). In Singapore, the selection for political office is based upon a high- rationalized system of merit involving academic credentials, job performance and

136 character evaluation. Potential candidates go through six sieves of informal tea meetings, formal interviews, and rigorous psychological testing (consisting over 1,000 questions) (Bellows, 2009). This stringent process of selection has the effect of legitimating the state in the eyes of the people, thus bestowing the state with a high level of prestige (Johnson, 1982).

Consequently, getting a good job within the state sector (which comprises the civil service, statutory boards and government-linked companies) is highly desired among Singaporeans. Critics have drawn attention to the fact that because the state monopolizes the nation’s talent pool, few outstanding individuals are left to the small business sector and multi-national companies (MNCs): that is, the state muscles out the other labour markets (Tan, 1996). But the state’s rebuttal is that without good leadership and governance, nothing else down the line works (Neo and Chen, 2007).

Indeed, the state has an elaborate system of rewards to attract the most talented. One established way has been the offering of lucrative government scholarships (usually to prestigious universities overseas) to students who have outperformed their peers in the national examinations in exchange for some stipulated number of years of bonded service (Barr, 2006). Another way has been the implementation of a civil service pay structure clearly stratified by academic performance. This pay structure allocates the most attractive rewards to the examination stalwarts. Less academically-inclined students are likely to end up in the large but less powerful private sector. On a scale of meritocracy, the state sector could be said to occupy the uppermost extreme position, the MNCs the middle, and the small business sector, the bottom position.

Many Singaporeans believe that academic credentials are on their own sufficient for securing a good job. This belief is reinforced by the pervasive rhetoric of meritocracy in Singapore which purports to allocate resources based on academic merit rather than ascriptive factors. In a 2004 national survey asking Singaporeans to rank how important various resources were to them, “education” was rated most important,

137 followed by “hard work” and “ability”, and then, only in fourth, “social connections” (Tan, 2004). This finding implies the perceived ineffectiveness of social capital as a means of social advancement in face of strong human capital idealization.

The academic system in Singapore is not just about students jostling for the best grades and resources, but about parents being very much involved as well (Cheah, 1998). While Confucian culture and its high emphasis on education is one source of this competition, (and in this regard, Singapore is no different from the other East Asian and Asian societies: Taiwan, Korea, Japan, China and India), in the case of Singapore, the state apparatus and its propensity to tightly link wage/salary structures to academic performance intensifies this credentialism all the more.

Part of it is culture: Singapore is a predominantly Chinese society (75%): the Chinese themselves have had a long history of academic credentialism and knowledge acquisition (Weber, 1983). But structure is also important (Sen, 2004). The value of education in the mainland was since early on, bound up with an intense Mandarinate system which selected state officials based on rigorous examinations testing knowledge on poetry and the Confucian classics. The best candidates were co-opted to serve in the emperor’s administration (Weber, 1983).

Corruption is strongly eschewed in Singapore’s state sector so that the taking of bribes is one of the mortal sins. In 1986, a cabinet minister was investigated by the Corrupt Practices Investigation Bureau (CPIB) for allegedly accepting two bribes of $500,000 each in 1981 and 1982. Although the minister maintained his innocence, he committed suicide before being charged for the offences. In his suicide note, he wrote:

I have been feeling very sad and depressed for the last two weeks. I feel responsible for the occurrence of this unfortunate incident and I feel I should accept full responsibility. As an honourable oriental gentleman I feel it is only right that I should pay the highest penalty for my mistake.

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The anti-corruption stance in Singapore is from the viewpoint of the state, not only important for ensuring social stability in society, but also for making Singapore a place of trustworthy institutions where citizens and foreign investors can safely invest their money.

With meritocracy and its strong emphasis on education for social mobility, many disadvantaged Singaporeans have been able to ascend the class structure. The provision of government subsidies for tertiary education has greatly facilitated this process of individual advancement (Chang, 1995). And yet, there are some aspects of the class structure, especially in the area of relative mobility, that the meritocracy has been less successful at equalizing. For example, tertiary subsidies were for a long time available to all tertiary students regardless of their family background. This created a situation where well-to-do students had access to the same incremental resources as less well-to-do students despite already having more to begin with.

Meritocratic intentions do not always lead to meritocratic outcomes. The fact that people inherit unequal starting lines in life and compete unequally based on them is seldom highlighted in the discourse of meritocracy (Gillis, 2005). In the end, merit- based systems are often likely, even if unintentionally, to pick people who are already advantaged in terms of their family background (also see Tan, 2008; Barr and Skrbis, 2008).

While many Singaporeans from humble backgrounds have excelled in the national examinations, such meritocratic occurrences may get increasingly rare as society develops and stratification between cosmopolitan rich and local poor becomes increasingly evident.

As to whether any society can be truly meritocratic at all is inherently debatable (Tilly, 1998; Gillis, 2005). But, the belief in meritocracy is itself a powerful force; and belief systems often culminate in institutional structures (Redding, 2008). In Singapore, the

139 contradictions of a meritocratic system are seldom discussed at the level of the nation. Instead, meritocracy is, as a pristine principle, venerated throughout society. To the Singapore state, meritocracy is the best way of administering society. One of the ruling party’s most influential members, S. Rajaratnam, once said: “I believe in a hierarchy of merit simply because I cannot think of any other way of running a modern society, for that matter even a primitive tribal society” (Chan and Haq, 1987 cited in Bellows, 2009).

HYPOTHESES

The question that drives this research is specifying the role of social capital in such a strong state and credentialistic society as Singapore. The main argument being advanced is that meritocratic constraints tend to suppress (in lieu of their anti- corruption stance) the role and value of “mobilized” social capital (i.e. job contacts), but they cannot suppress the role and value of “accessed” social capital. While a meritocracy may tend to suppress overt forms of network mobilization (e.g. Chua, 2010), it cannot prevent social capital from working in more embedded ways. My data will demonstrate that social capital matters very much, even in meritocratic jobs. In a merit-based society that generally frowns upon job recruitment based on overt network mechanisms, the role of accessed social capital, being more embedded, becomes especially important.

My hypotheses will be stated as follows:

H1: Social capital facilitates entry into highly-meritocratic jobs primarily through the invisible hand of social capital (i.e. accessed social capital) rather than the visible hand of social capital (i.e. use/mobilization of job contact).

H2: The invisible hand of social capital (i.e. accessed social capital) is on average a more powerful facilitator of job success than the visible hand of social capital (i.e. use/mobilization of job contact).

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H3: The positive impact of the invisible hand of social capital (i.e. accessed social capital) on job success is especially pronounced in labour markets that emphasize meritocracy (e.g. in the state sector).

H3 implies interaction effects. Based on the argument that embedded forms of social capital continue to matter greatly in meritocratic labour markets, we should expect to see accessed social capital being especially effective as a generator of earnings in meritocratic jobs. Statistically, this means that relative gains in earnings accrued from using accessed social capital should be significantly greater in meritocratic jobs than in non-meritocratic jobs. A possible explanation (concerning why accessed social capital should be more efficacious in meritocratic sectors) is that meritocratic jobs may tend to be more challenging, and hence people with better social resources would tend to do better.

DATA AND METHODS

Data sources and sample

I analyze representative data from the 2005 Project Network Survey, using a sub-sample of 656 currently employed Singaporean adults aged between 25 and 55. As labour markets and current earnings are important variables in the analysis, I included only part-time employed (9%) and fully employed (91%) respondents, excluding homemakers, students and the retired (Table 1).

Men and women contributed to 58.4% and 41.6% of the sample respectively. The uneven gender distribution is due to men’s greater participation in paid work relative to women. As the numerically dominant ethnic group, Chinese make up the majority 67.8% of the sample, while Malays and Indians were oversampled to make up 18.6% and 13.6% respectively.

The survey distinguished between three educational groups: 25.0% have ‘low’ level education (i.e. no formal education or some secondary education), 40.9% have ‘middle’

141 level education (i.e. completed secondary school, technical school or pre-university), and 34.2% have ‘high’ level education (i.e. polytechnic or university graduate).

Of the 656 respondents, 24.3% were employed in the state sector (comprising the civil service, statutory boards and government-linked companies), 20.3% in the MNC sector and 55.4% in the small business sector. 48.9% were employed as professionals, managers or technicians (PMT), 25.6% as clerical or service workers and 25.5% as workers in production, plant, and cleaning etc.

As in Fischer’s Northern Californian study (Fischer, 1982), this survey used a range of name generators (e.g. who do you discuss important matters) to delineate the personal networks of the respondents. The name generators were followed up with name interpreters (Marsden, 2005), which elicited information about each network member and the nature of their relationship with their respondent. These name interpreters included items such as network members’ gender, race, age, education, housing type, in addition to tie information such as the role relationship (e.g. whether child, parent, spouse, sibling, co-worker etc.) closeness, and tie longevity.

The name generators were designed to cover a range of emotional, social and instrumental scenarios with the exact wordings modified to suit the Singapore context. The data was collected by a reputable and experienced survey research company in Singapore, AC Nielsen, and conducted in three possible languages, English, Mandarin or Malay. Each interview lasted about an hour, and was conducted at the door of the respondents’ homes.

Accessed and mobilized social capital

I used three measures of accessed social capital: 1) number of university graduates 2) number of private housing dwellers and 3) number of Chinese. Given that university education, private property and Chinese ethnicity are all high status resources in Singapore (Lee, 2006), they make excellent measures of social capital. The first two are

142 high on the SES ladder while the third is high on the ethnic status ladder (Weber, 1946). Even though education, private property and Chinese are statistically interrelated, they are by no means perfectly correlated. These distinguishable measures offer an excellent opportunity to evaluate the extent to which different kinds of high-status social capital affect job success.

TABLE 1. SAMPLE CHARACTERISTICS (N = 656)

PERSONAL CHARACTERISTICS OF RESPONDENTS PERCENTAGE (%)

AGE: 25 -29 years 11.9 30 -34 years 16.2 35 -39 years 17.4 40 -44 years 23.3 45 -49 years 17.7 50 -55 years 13.6

GENDER: Male 58.4 Female 41.6

ETHNIC GROUP: Chinese 67.8 Malay 18.6 Indian 13.6

EMPLOYMENT STATUS: Full -time 91.0 Part -time 9.0

EDUCATION: ‘Low’ education (No formal education or some secondary ) 25.0 ‘Middle’ education (Co mpleted secondary, technical school 40.9 or pre-university) ‘High’ education (Polytechnic or university graduate) 34.2

JOB SECTOR: Small business sector (SMEs) 55.4 Multinational companies (MNCs) 20.3 State sector (civil service, statutory boards and GLCs) 24.3

OCCUPATION: Professional, Managerial, Technical (PMT) 48.9 Clerical and Service 25.6 Production, Plant, Cleaning etc. 25.5

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Mobilized social capital is operationalized as a dichotomous variable measuring whether (1) or not (0) the respondent had activated a job contact during his/her job search. Following Granovetter’s original design (1974), the survey asked respondents to report how they had obtained their current jobs. The options were: 1) I saw an advertisement in a newspaper (or other sources of media) 2) I found out through an employment agency 3) I submitted an application 4) Someone I didn’t know contacted me and said that I had been recommended 5) I asked friend/person who told me about the job 6) A friend/person who knew I was looking for a job contacted me 7) A friend/person who didn’t know I was looking for a job contacted me and 8) Others. Respondents who indicated options 5, 6 or 7 were assigned ‘1’ on the job contact variable; the rest were assigned ‘0’.

Job sector

The job sector variable includes three kinds of labour markets, each differing by the extent to which meritocracy is enforced. The most meritocratic job sector is the state sector, followed by the multinational companies (MNCs), and then the small business sector (SMEs), in that order. Depending on the hypothesis being tested, job sector is either a dependent (H1) or independent variable (H2 and H3).

The testing of H1 evokes a series of multinomial logistic regression models estimating the impact of accessed social capital (the three kinds) and mobilized social capital on the logged odds of being in the various job sectors.

Earnings

Earnings is used as a dependent variable and deployed in several OLS regressions. To transform the skewed distribution, I applied a square root to the numeric codes representing each of seventeen earning categories. These OLS regressions are used to test H2, which hypothesizes that in Singapore’s meritocratic society, accessed social capital is a more powerful facilitator of job success than mobilized social capital.

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Other predictors of earnings

Additional predictors of earnings include education, gender, race, age, employment (part time or full time), occupation, job sector, and participation in voluntary organizations.

Education is computed as two dummy variables: ‘education (middle)’ and ‘education (high)’, with education (low) being the reference category. ‘Female’ is a dummy variable for self-reported gender: 1 for female and 0 for male. Race is represented by two dummy variables: ‘Chinese’ and ‘Indian’, with Malay being the reference category. As earnings tend to peak in midlife and taper off after, age is entered in linear and quadratic forms. Employment status is a dummy variable for whether the respondent is part time or full time employed, 1 for part time and 0 for full time. Occupation is represented by two dummy variables: ‘PMT’ (Professional, Managerial and Technical) and ‘Clerical/Service’; the omitted category is Production, Plant and Cleaning etc. Job sector is represented by two dummy variables: ‘state sector’ and ‘MNC sector’, with small business sector assigned the reference category. ‘Social participation’ is a dummy variable for participation in voluntary associations, 1 for participation and 0 for nil.

Interaction effects

H3 (that the positive impact of accessed social capital on job success is especially pronounced in labour markets which emphasize meritocracy) implies interaction effects. Taking the small business sector as the reference category, I computed the following interaction terms: [accessed social capital] X [state sector], [accessed social capital] X [MNC sector] and [mobilized social capital] X [state sector], [mobilized social capital] X [MNC sector]. Assuming that H3 is supported, we would expect 1) [accessed social capital] X [state sector] to be positive and significant, and 2) [mobilized social capital] X [state sector] to be either negative and significant, or less positive and significant.

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RESULTS

1) Accessed social capital is more likely than mobilized social capital (i.e. use of job contact) to facilitate entry into meritocratic job sectors

Tables 2, 3 and 4 are multinomial logistic regressions estimating the impact of accessed and mobilized social capital on entry into the various job sectors.

These tables test H1 across three different types of accessed social capital: number of university graduates (Table 2), number of private housing dwellers (Table 3) and number of Chinese (Table 4).

Control variables have been added in order to isolate the independent effects of accessed and mobilized social capital on job sector. Let me discuss Table 2 in detail and then (discuss) Tables 3 and 4 in relation to Table 2.

Table 2 indicates that:

1) Accessed social capital (.48***) is associated with entry into the state sector (versus small business sector).

2) Accessed social capital (.25*) is associated with entry into the MNC sector (versus small business sector).

3) Accessed social capital (.23) is associated with entry into both the state and MNC sectors.

4) Mobilized social capital (- 1.01***) is associated with entry into the small business sector (versus state sector).

5) Mobilized social capital (- .20) is associated with entry into the MNC and small business sectors.

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6) Mobilized social capital (- .81**) is associated with entry into the MNC sector (versus state sector).

Bringing these results together, we may discern three interesting patterns: 1) accessed social capital goes with state sector jobs, 2) mobilized social capital goes with small business sector jobs, and 3) MNC jobs go with both accessed and mobilized social capital.

These are important results because they illustrate how different kinds of social capital go with different kinds of job sectors. For example, the more meritocratic the labour market, the more salient the role of accessed social capital (i.e. the invisible hand of social capital). In comparison, the less meritocratic the labour market (e.g. in small business sector jobs), the more salient the role of contact use (which is the visible hand of social capital). The reason why MNCs straddle both accessed and mobilized social capital is that MNCs are most likely (relative to state and small business sectors) to comprise a combination of formal and informal structures (Ritchie, 2009).

As the data is cross-sectional, we run into the problem of causality. That is, there is no guarantee that the networks being examined (e.g. accessed social capital) were formed prior to respondents’ entry into paid work. In fact, it may be argued that the networks of older workers must be in part formed through their jobs. Hence one important limitation of this study is the absence of longitudinal data.

The results in Table 3 (where accessed social capital is number of ‘private housing dwellers’) replicate those in Table 2. Although the exact coefficients differ, their patterning and therefore conclusions are exactly the same. A plausible reason for this is the high correlation between education and private housing as high SES resources in Singapore.

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The results in Table 4 are different from those in Tables 2 and 3. The most salient difference is the null association between Chinese social capital and entry into state sector jobs (.05). This result suggests that ethnicity in itself is not a resource (for entering the lucrative state sector), whereas education and wealth are. As there can be many disadvantaged individuals within a single high status ethnic group such as Chinese, high ethnic group status is not a direct enough measure/proxy of resources.

TABLE 2. MULTINOMIAL LOGISTIC REGRESSION ESTIMATING THE EFFECTS OF ACCESSED (# OF UNIVERSITY GRADUATES) AND MOBILIZED SOCIAL CAPITAL (CONTACT USE) ON JOB SECTORS

PREDICTORS Logged odds of Logged odds of being Logged odds of being being in the state in the MNC sector in the state sector sector versus small versus small business versus MNC sector business sector sector

Accessed social capital .48*** .25* .2 3 (as # of university graduates) (1.62) (1.29) (1.26)

Mobilized social capital - 1.01*** - .20 - .81** (Job contact) (.37) (.82) (.44)

Education (mid) .93** .27 .66† (2.53) (1.32) (1.93)

Education (high) .88* .72* .16 (2.42) (2.05) (1.17)

Female .26 .00 .26 (1.30) (1.00 ) (1.30)

Chinese - 1.01*** - .21 - .80* (.37) (.82) (.45)

Indian .35 .31 .04 (1.42) (1.37) (1.04)

Age .20** .01 .19* (1.23) (1.01) (1.21)

Intercept - 1.61 - 1.05 Change in -2LL 120.12*** 120.12*** N = 654 OMITTED CATEGORIES. – Did not use job contact, Male, Malay, Education (low). *P < .05 **P < .01 ***P < .001 (two tailed tests) (Odds ratio in parentheses)

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All the above results generally strongly support H1: that social capital facilitates entry into highly-meritocratic jobs through the invisible hand of social capital rather than the visible hand of social capital, however, with an important caveat: it is high-SES social capital (education and wealth) rather than high ethnic status social capital that is especially likely to facilitate entry into those meritocratic jobs.

That is, being ‘Chinese’ is not a factor in entering a meritocratic job, but rather being well-educated or its high correlate, being wealthy is. On its own, the category Chinese is not valuable unless accompanied by high-SES resources. It appears at least in the context of Singapore, that it is predominantly class and SES resources that more fully explain variations in life chances, rather than more diffusely, ethnic culture per se.

2) Accessed social capital is on average a more powerful facilitator of job success than mobilized social capital (i.e. contact use)

Tables 5 to 7 are a series of step-wise OLS regression models estimating the effects of accessed and mobilized social capital on earnings. Each table estimates the impact of a different kind of accessed social capital, beginning with ‘number of graduates’ (Table 5), followed by ‘number of private housing dwellers’ (Table 6), followed by ‘number of Chinese’ (Table 7).

Each table estimates five models, the first three are main effects models, the last two are models which incorporate interaction effects. Concerning the main effects models, Model 1 estimates the effects of accessed and mobilized social capital (without controls). Model 2 inserts the effect of education as a control, because 1) theoretically, education should be all that matters in a meritocracy and 2) because education is highly correlated with access to social capital. The point is to test if there are any social capital effects on earnings independent of education effects. Model 3 includes other control variables which potentially impact earnings (such as gender, ethnicity, age, age square as a proxy for work experience etc.).

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TABLE 3. MULTINOMIAL LOGISTIC REGRESSION ESTIMATING THE EFFECTS OF ACCESSED (# OF PRIVATE HOUSING DWELLERS) AND MOBILIZED SOCIAL CAPITAL (CONTACT USE) ON JOB SECTORS

Accessed social capital .28** .21* .07 (as # of private housing (1.33) (1.24) (1.07) dwellers)

Mobilized social capital - 1.04*** - .23 - .81** (Job contact) (.36) (.79) (.44)

Education (mid) .89** .23 .66 (2.43) (1.26) (1.93)

Education (high) 1.34*** .88** .46 (3.80) (2.41) (1.58)

Female .32 .04 .28 (1.38) (1.04) (1.32)

Chinese - .93*** - .22 - .71* (.39) (.80) (.49)

Indian .41 .33 .08 (1.51) (1.39) (1.08)

Age .15* - .02 .17* (1.16) (.98) (1.19)

Intercept - 1.66 - .95 Change in -2LL 109.10*** 109.10***

N = 653 OMITTED CATEGORIES. – Did not use job contact, Male, Malay, Education (low). *P < .05 **P < .01 ***P < .001 (two tailed tests) (Odds ratio in parentheses)

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TABLE 4. MULTINOMIAL LOGISTIC REGRESSION ESTIMATING THE EFFECTS OF ACCESSED (# OF CHINESE) AND MOBILIZED SOCIAL CAPITAL (CONTACT USE) ON JOB SECTORS

Accessed social capital .05 .04 .01 (as # of Chinese) (1.05) (1.04) (1.01)

Mobilized social capital - 1.02*** - .21 - .81** (Job contact) (.36) (.81) (.44)

Education (mid) 1.03*** .32 .71 (2.79) (1.37) (2.03)

Education (high) 1.70*** 1.13*** .57 (5.48) (3.11) (1.77)

Female .31 .04 .27 (1.37) (1.04 ) (1.31)

Chinese - 1.01** - .31 - .70 (.37) (.73) (.50)

Indian .40 .31 .09 (1.49) (1.36) (1.09)

Age .20** .01 .19* (1.22) (1.01) (1.21)

Intercept - 2.43 - 1.50 Change in -2LL 100.68*** 100.68***

N = 654 OMITTED CATEGORIES. – Did not use job contact, Male, Malay, Education (low). *P < .05 **P < .01 ***P < .001 (two tailed tests) (Odds ratio in parentheses)

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Table 5 provides compelling evidence that accessed social capital (as number of university graduates) is a more powerful facilitator of job success than mobilized social capital. For example, model 2 indicates that net of education, accessed social capital is linked with higher earnings (.10***), while mobilized social capital is associated with lower earnings (- .09**). With still further controls added in model 3, the positive and significant effect of accessed social capital remains (.08***), suggesting that accessed social capital (in the form of number of university graduates) has a highly independent effect on status attainment.

Table 6 indicates similar results. Accessed social capital (this time as ‘number of private housing dwellers’) is associated with greater earnings (.12*** in model 3), while mobilized social capital is associated with lower earnings (- .06* in model 3).

The results in Table 7 are similar to Tables 5 and 6, in that net of education, accessed social capital (as ‘number of Chinese’) is linked with higher earnings (.01* in model 2) and mobilized social capital is linked with lower earnings (- .11** in model 2).

However there are important differences: for example, the effect of number of Chinese on earnings (.01* in model 2 of Table 7) is less prominent than the effects of university graduates (.10*** in model 2 of Table 5) and private housing dwellers (.14*** in model 2 of Table 6). And in fact, the relationship between number of Chinese and earnings disappears when further controls are added (.01, model 3 of Table 7).

The latter results suggest that high ethnic status social capital is a less powerful source of status attainment than high SES social capital. They also suggest that direct measures of resources (such as access to contacts with education and wealth) are better predictors of job success than are indirect measures of resources such as high status ethnic group membership. That is, it is not Chinese culture (as a symbolic form of power per se) that influences labour market outcomes, but access to education and wealth that matters.

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TABLE 5. OLS REGRESSION ESTIMATING THE EFFECTS OF ACCESSED (# OF UNIVERSITY GRADUATES) AND MOBILIZED SOCIAL CAPITAL (CONTACT USE) ON EARNINGS

PREDICTORS 1 2 3 4 5

Accessed social capital .22*** .10*** .08*** .04† .08*** (as # of university graduates)

Mobilized social capital - .16*** - .09** - .05 - .04 - .03 (Job contact)

Education (middle) .32*** .23*** .23*** .23*** Education (high) .69*** .54*** .55*** .54***

Female - .18*** - .18*** - .18*** Chinese .02 .02 .01 Indian .01 .01 .00 Age .06*** .06*** .06*** Age squared - .02*** - .02*** - .02*** Employed (part time) - .43*** - .43*** - .42*** PMT .32*** .33*** .32*** Clerical/service .11* .11* .11* MNC sector .11** .16*** .10* State sector .06 .11** .08* Social participation .00 .00 .01

[Accessed SC] X [MNC] .07* [Accessed SC] X [State] .08** [Mobilized SC] X [MNC] .04 [Mobilized SC] X [State] - .13

Constant 2.62 2.14 2.14 2.08 2.14 R square .29*** .42*** .60*** .61*** .60***

N = 656 OMITTED CATEGORIES. – Did not use job contact, Male, Malay, Education (low), No involvement in voluntary organizations, small business sector. †P < .10 *P < .05 **P < .01 ***P < .001 (two tailed tests) (Standard errors upon request)

3) Accessed social capital is especially valuable in highly-meritocratic job sectors

Tables 5, 6 and 7 indicate (in their respective model 4) positive interaction effects on [accessed social capital] x [MNC], and [accessed social capital] x [state], suggesting that

153 the invisible hand of social capital (i.e. university graduates, private housing dwellers and Chinese) is especially likely to facilitate job success in meritocratic jobs.

TABLE 6. OLS REGRESSION ESTIMATING THE EFFECTS OF ACCESSED (# OF PRIVATE HOUSING DWELLERS) AND MOBILIZED SOCIAL CAPITAL (CONTACT USE) ON EARNINGS

PREDICTORS 1 2 3 4 5

Accessed social capital .24*** .14*** .12*** .09*** .12*** (as # of private housing dwellers)

Mobilized social capital - .23*** - .12*** - .06* - .05 † - .06 (Job contact)

Education (middle) .30*** .21*** .21*** .20*** Education (high) .69*** .54*** .54*** .54***

Female - .17*** - .17*** - .17*** Chinese - .00 .00 - .01 Indian .02 .03 .02 Age .05*** .05*** .05*** Age squared - .02*** - .02*** - .02*** Employed (part time) - .42*** - .41*** - .41*** PMT .31*** .32*** .31*** Clerical/service .10* .10* .10* MNC sector .10** .14*** .08† State sector .06† .10** .08* Social participation - .02 - .02 - .01

[Accessed SC] X [MNC] .05* [Accessed SC] X [State] .06* [Mobilized SC] X [MNC] .06 [Mobilized SC] X [State] - .11

Constant 2.65 2.19 2.20 2.16 2.20 R square .30*** .47*** .63*** .64*** .63***

N = 655 OMITTED CATEGORIES. – Did not use job contact, Male, Malay, Education (low), No involvement in voluntary organizations, small business sector. †P < .10 *P < .05 **P < .01 ***P < .001 (two tailed tests) (Standard errors upon request)

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TABLE 7. OLS REGRESSION ESTIMATING THE EFFECTS OF ACCESSED (# OF CHINESE) AND MOBILIZED SOCIAL CAPITAL (CONTACT USE) ON EARNINGS

PREDICTORS 1 2 3 4 5

Accessed social capital .04*** .01* .01 - .00 .01 (as # of Chinese)

Mobilized social capital - .26*** - .11** - .05 - .04 - .03 (Job contact)

Education (middle) .34*** .23*** .24*** .23*** Education (high) .86*** .66*** .65*** .66***

Female - .17*** - .17*** - .17*** Chinese .03 .02 .02 Indian .01 .02 .01 Age .06*** .06*** .06*** Age squared - .02*** - .02*** - .02*** Employed (part time) - .42*** - .42*** - .41*** PMT .35*** .35*** .34*** Clerical/service .12** .12* .12* MNC sector .12** .01 .12* State sector .09* - .01 .11** Social participation .02 .02 .02

[Accessed SC] X [MNC] .02* [Accessed SC] X [State] .02* [Mobilized SC] X [MNC] .01 [Mobilized SC] X [State] - .12

Constant 2.34 1.96 1.98 2.02 1.97 R square .09*** .40*** .59*** .59*** .59***

There are no significant interaction effects concerning [mobilized social capital] x [MNC] and [mobilized social capital] x [state] in all three tables (model 5). However, the negative coefficients of [mobilized social capital] x [state] appear to be quite sizable across them (i.e. - .13, - .11 and - .12 in Tables 5, 6 and 7 respectively with p-values ranging from .12 to .15), suggesting that mobilized social capital (in the form of contact

155 use) tends to be rather useless, particularly in meritocratic jobs. These latter findings juxtaposed with the positive interaction effects on accessed social capital, reinforce the idea that embedded forms of social capital are much more leveraging than overt forms of network mobilization in meritocratic jobs.

The greater relative payoffs to accessed social capital in meritocratic job sectors may be due to meritocratic jobs being in general more challenging, and thus people who are well-connected are more likely to do well on the job. But another explanation, which I have emphasized in this paper, is that social capital, particularly in the embedded form, continues to be highly leveraging under meritocratic conditions.

DISCUSSION

The goal of this paper has been to understand the interrelationship between labour markets varying by levels of meritocracy and the role and payoffs to social capital in those labour markets. Evoking the case of Singapore, a society characterized by a highly-meritocratic core of labour markets, but supplemented by a ring of less meritocratic labour markets, I ask: how do meritocratic constraints influence the role and value of mobilized and accessed social capital? In labour markets that emphasize formal credentials and meritocratic ways of recruitment, does social capital in fact cease to matter? If social capital continues to matter, how so?

In a previous paper (Chua, 2010), I discovered three important characteristics regarding the utilization of job contacts in Singapore. I found that 1) job contacts were rarely utilized to enter highly-meritocratic jobs; 2) they were associated with lower earnings and 3) they were associated with lower levels of education. I reasoned that job contacts were not popular because of the high value and attention paid to academic credentials in highly-meritocratic jobs. This current paper provides an important addendum: the fact that job contacts are seldom used to enter meritocratic jobs does not automatically mean that social capital has no role in meritocratic jobs. Job contacts may not matter much in meritocratic hiring, but broader forms of social networking certainly do.

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Granted, education is important in the meritocracy, but social networks are themselves strong predictors of education (Coleman, 1988, Erickson, 1996): we learn from our networks how to do well in school, how to present ourselves during interviews, how to be an effective employee on the job, how to file an application etc, and all these help to facilitate entry into a meritocratic job. Taking an embedded view of social networks means that social capital and meritocracy need not be mutually exclusive.

On the question of meritocracy, the multinational companies (MNCs) pose an interesting case as they comprise a combination of formal and less formal elements. On one hand, they do not have the strict formality of state bureaucracies. On the other hand, they are not like small-scale businesses, that is, they straddle a middle ground between formal bureaucracies and small businesses. If accessed social capital goes with high meritocracy and mobilized social capital goes with low meritocracy, then we would expect MNCs to go with a combination of accessed and mobilized social capital. And that is exactly what I find.

Embedded social resources facilitate job success

According to the OLS regressions in Tables 5, 6 and 7, accessed and mobilized social capital lead to significantly better and lower earnings respectively, suggesting that the leveraging power of social networks manifests primarily through embedded rather than overt social capital.

Although the list could be endless, embedded social capital may be thought to imply the following resources: 1) unsolicited routine job information (Lin, 2000; Lin and Ao, 2008), 2) network-induced human capital (Coleman, 1988), 3) network-induced cultural capital (Bourdieu, 1986), 4) network-induced diverse knowledge (Erickson, 1996), and 5) network-induced bright ideas (Burt, 2004) -- all of which could help facilitate job success significantly.

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The point here is that people may often benefit from networks without consciously seeking to do so. Their enhanced job success is not the result of a conscious angling for advantage, but an unanticipated outcome of being embedded in good connections (Small, 2009). That is, people are reaping social networking benefits without actually intending to do so.

Direct measures of high status resources, such as ‘number of graduates’ and ‘number of private housing dwellers’, are especially likely to facilitate job success. Correlated measures such as ‘number of Chinese’ are less powerful predictors, probably because of sizable education and wealth heterogeneities within high status ethnic groups. Being Chinese is not a resource on its own, unless accompanied by high education and personal wealth.

Embedded social resources especially efficacious in meritocratic jobs

The positive interaction effects involving accessed social capital and the marginally negative interaction effects involving mobilized social capital in Tables 5, 6 and 7 constitute strong evidence that social capital works primarily through the invisible hand of accessed social capital rather than the visible hand of mobilized social capital in meritocratic labour markets.

Meritocratic constraints do not spell the end of social capital. If we are prepared to consider the role of embedded network resources, in addition to job contacts, we will see how important the former are in facilitating job success. Indeed, meritocratic constraints do not relegate social capital to a marginalized role, but inflects it with a role that is at once embedded, but pervasive, and effective.

The embedded yet effective role of the invisible hand of social capital implies contradictions within a system of meritocracy. If we go by the logic that education should be all that matters in an ideal-typical meritocracy, then the fact that social capital

158 effects show up as positive and significant (despite controls for education), suggests that meritocracies are networked societies.

The fact that job contacts tend to be ineffective in the most meritocratic of job sectors, does not mean that other forms of networking are lacking or absent. As my data has shown, accessed social capital is an important predictor of job success, even and especially so in jobs which stress meritocracy. So then, in a real-life meritocracy, unequal labour market outcomes are not just the result of unequal access to education alone, but unequal access to broad bases of social capital as well.

The rhetoric of meritocracy in its striving for legitimation tends to privilege the important role of human capital, while at the same time, downplaying the role and value of social networking. Yet as this paper has shown, social capital contributes significantly to status attainment (and hence inequality reproduction) even in the most meritocratic of job settings.

CONCLUSION

When analyzing social capital, it is important to consider not only the networks that are consciously mobilized in specific situations such as job searches, but also the broader networks which people do not mobilize, but have access to (Lin, 2001). Indeed, the use of a contact in a job search is at best a small and partial representation of a network, and thus is not representative of the total capacity of a person’s social resources (Lin and Ao, 2008:111). The task of this present paper has been to understand how mobilized and accessed forms of social capital jointly operate to affect status attainment in the context of labour markets varying by levels of meritocracy.

Theoretically, this paper emphasizes the importance of institutional forces influencing the role and value of social capital in labour markets. Evoking Singapore as a case study, I show that in labour markets that emphasize meritocracy, social capital tends to facilitate job success through accessed resources rather than mobilized resources. That

159 is, in labour markets that allocation rewards by fair-play and merit, the workings of social capital tend to be more subtle than overt.

This paper stresses a contextual element to the study of social capital. At the end of the day, it is not just social resources per se that influence status attainment, but equally important, the a priori role of institutional factors impacting how much or how little those social resources pay off. To add to the conventional ‘investments’ rhetoric of social capital research (Lin, 2001), a more comprehensive study of social capital would have to include an analysis of the conditional role of institutional constraints on social capital, in addition to individual factors.

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Chapter 6 Conclusion

Context matters

When Granovetter (1985) wrote his important theoretical article on economic sociology, he argued that sociologists, and in particular economists, needed a more relationally focused view of economic action extending beyond individual action and rational choice models. The fact that markets are often characterized by human cooperation and competition, rather than atomism or social isolation (Uzzi, 1996) signals a need for economic theories that are more relationally constituted.

But this invites a further question -- are analyzing networks in themselves sufficient for generating a comprehensive understanding of economic action? The broad aim of my three essays has been to verify the importance of networks, but also to extend the works of Granovetter (1985), by suggesting that the study of networks be further anchored to broader socio-historical frames of reference. By evoking aspects of social organization: politics, economy, culture and society, my essays have sought to underscore the importance of institutions as sources of the distribution, role and value of social capital.

The first paper (Chapter 3) highlighted two interesting results: 1) dominant gender and ethnic groups tend to have more social capital than less dominant gender and ethnic groups; and 2) ethnic and gender groups tend to access distinctive forms of social capital. Distinctive patterns of network inequalities by gender and ethnicity are shown to be partially due to the distinctive patterns of access that gender and ethnic groups have to organizational settings such as schools, paid work and voluntary association. These organizational settings may sometimes generate social capital more efficaciously for some individuals/social groups.

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The second paper (Chapter 4) moved from analyzing sources of social capital to analyzing consequences of social capital. The paper showed that in certain sectors, such as the state bureaucracy, social networking brings no distinctive advantages as appointments are made exclusively on the basis of the academic credentials of the candidates. That is, personal contacts are not always useful, especially in labour markets that rely heavily on the signalling role of academic credentials to match people to jobs.

The third paper (Chapter 5) is a build-up from the second paper. It argued that the ineffectiveness of job contacts in meritocratic labour markets is not necessarily a sign that social capital is irrelevant in contexts of meritocracy. The data showed that in meritocratic job sectors, social capital facilitates status attainment primarily through “accessed” social capital rather than “mobilized” social capital. That is, the status attainment role of social capital in contexts of meritocracy tends to be more embedded than overt.

Singapore as an excellent case study reflecting broader theoretical concerns

The interesting characteristics of Singapore society: as 1) meritocratic and yet elitist, 2) multicultural and yet racially-ordered and 3) progressive and yet patriarchal, provided an excellent opportunity for studying the link between macro-level conditions and individuals’ experiences with social capital. My papers demonstrated that structural factors are important aspects of the distribution, role and value of social capital, and that what appear as cultural differences may in fact be institutional differences.

Although I have focused on Singapore as an anchoring case, my papers have at various points, evoked data from countries such as the United States to provide a comparative lens. While specifying the macro-micro link forms the overarching task and basis of the dissertation, each paper contains finer theoretical contributions that speak to specific issues in the literature on social capital. Broadly, the dissertation had delved into two

166 sets of research questions. The first set of questions pertain to sources of social capital: how is social capital distributed among gender and ethnic groups and more importantly, what is it about the social organization of gender and race that result in social capital being stratified along gender and racial lines?

The second set of questions pertain to consequences of social capital: what does social capital accomplish for people? What are the role and payoffs to different kinds of social capital in different kinds of labour markets? Does social capital cease to be important in labour markets that are meritocratic? To what extent does social capital work through the invisible hand rather than the visible hand in meritocratic markets?

Unequal networks

Organizational settings such as schools, paid work and voluntary associations are fertile ground for the accumulation of social capital. The unequal access to social capital among gender and ethnic groups is really a function of their unequal access to organizations that matter for network formation. In addition to having more social capital in general, dominant gender and ethnic groups may often access distinctive forms of social capital respectively.

My data showed that whereas men tend to have higher access to forms of social capital such as non-kin and weak ties (but not well-educated and wealthy social capital), dominant ethnic groups tend to have greater access to forms of social capital such as well-educated and wealthy ties (but not non-kin). How should we explain such distinctive patterns: that is, how and why do ascriptive forms of stratification lead to such characteristic forms of network inequalities?

My data illustrated that ethnic groups’ unequal access to education (but equal access to paid work) and gender groups’ unequal access to paid work and voluntary associations (but equal access to education) account for much of why men and women, Chinese, Malays and Indians tend to have such distinctive forms of social capital.

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To be sure, the exact nature of the relationship between ascriptive categorical forms of stratification and access to organizations will be expected to vary depending on the actual conditions of specific societies. In countries like Japan, inequalities in education continue to be quite strong among gender groups, while in the United States, inequalities in education are especially stark among ethnic groups (especially between blacks and whites) (Kao, 1995). There will be variations in the characteristic types of social capital that gender and ethnic groups have access to, depending on societal variations in gender and ethnic groups’ access to organizational settings where social capital is formed.

The involved nature of my results signals a need for going deeper into the details, because in reality, the distribution of social capital is more complex than simple. There are several kinds of social capital that are potentially useful in labour markets, and powerful gender and ethnic groups have greater access to only specific kinds of them. So then, questions concerning the distribution of social capital should be posed in a more nuanced way: instead of asking: who has more social capital? (as if there was only one type of social capital), researchers should ask more carefully: who has more of what types of social capital and why ?

Job contacts, accessed social capital and status attainment

It is difficult to know the effects of social capital on status attainment without first asking at least three questions: 1) what kinds of social capital are we talking about? 2) what kinds of labour markets are being analyzed? and 3) who benefits from social capital?

The contingent nature of the role of social capital is exemplified by my data showing that whereas job contacts are often useless in meritocratic labour markets, they remain substantially useful in less meritocratic labour markets. Job contacts are more useful among low-educated job seekers and for entering jobs in industries such as wholesale,

168 retail, hotels, restaurants and construction. By contrast, highly-educated job seekers are more likely to rely on their credentials than their contacts for entering jobs.

The theoretical distinction between liberal and coordinated markets (Hall and Soskice, 2001) provides a useful framework for explaining the conditional role and value of job contacts in labour markets varying by levels of meritocracy. Meritocratic labour markets are coordinated structures because credentials are so closely tied to employment outcomes. As employers in CME job sectors tend to emphasize educational qualifications, job contacts have little room to influence the recruitment and remuneration process. The situation is different in LME job sectors, where a combination of formal qualifications and networks are invoked in the hiring process.

The liberal-coordinated distinction also sheds light on why job contacts are more likely to be mobilized in countries like the United States as compared to Singapore. While the active use of job contacts in the United States may often present itself on the surface as a culture of networking, factors such as the loosely-coupled link between education and labour markets are structural foundations of this networking ‘culture’ (Swidler, 1986).

Invisible networks and meritocracy

The meritocratic discourse -- that only effort and ability matter for getting ahead -- is contradicted by evidence showing that accessed forms of social capital remain extremely important for entering meritocratic jobs, even as mobilized forms of social capital may often be less useful.

This invites the question: why does social capital work subtly in contexts of meritocracy? One answer is the conceptual incompatibility between meritocracy and networking as value systems. Overt ways of social networking often imply negative characteristics such as: unethical, ulterior and schmoozing -- and these meanings are antithetical to the ideological tenets of meritocracy where themes such as impartiality, hiring based on ability not connections, and fairness, are upheld.

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In a meritocratic world, embedded forms of social capital, possibly taking the form of unsolicited job information and network-induced forms of cultural capital (and parental influence) are much more likely to facilitate status attainment than overt forms of network mobilization. Indeed, the politics of getting ahead in life in the context of a meritocracy is not solely a matter of angling or manipulating networks for some specific advantage, but more about being embedded in networks that in the routine course of everyday life turn out to be beneficial and important for the person.

A meritocratic society is not a place where individuals are single-mindedly engaged in a Hobbesian struggle for academic rewards, but more likely a society where connections are established in schools, work and voluntary associations, and where individuals who are embedded in them, find themselves with better life chances. Indeed, embedded forms of social capital are significant sources of social advantage and should be further researched, in addition to overt forms such as job contacts (Lin and Ao, 2008).

As access to human capital and social capital are closely intertwined with family background and upbringing (Coleman, 1988), network and cultural disadvantages originating from birth are often highly durable and difficult to eradicate, even as meritocratic processes aim to equalize opportunities for as many as possible (Tilly, 1998). Individuals with influential family backgrounds are often able to secure big advantages through social capital. In turn, these networks facilitate academic achievement. When someone does well in school, it is not always due to his/her own efforts alone, but the social and academic support that he/she receives from peers, family, teachers and professors, in addition to personal effort.

Reproduction of inequalities through social capital

In a merit-based system, the invisible hand of social capital is a significant source of social stratification. That is, the winners in a meritocracy are not those with sterling academic results alone, but those who also have sterling results and networks. Human capital and social capital, while analytically distinct, are really much more integrated in

170 everyday life. A good education and having highly-educated networks make for a powerful combination in meritocracies as the two are highly leveraging resources (Coleman, 1988).

In this regard, lower-educated individuals are doubly disadvantaged. First, low levels of education do not augur well in a merit-based system. Second, based on the principle of homophily, lower-educated individuals are significantly less likely (than their higher-educated counterparts) to have access to well-educated networks (McPherson, Smith-Lovin and Cook, 2001). The practice of early academic streaming in Singapore gives rise to a situation where the bright are put together with others like them, just as the non-achievers are put with others like them. The result is segregated classrooms, schools, and eventually networks.

Michael Young (1958) was right in predicting the widening gulf of elites and masses in meritocratic society. A significant contribution of social capital research is the demonstration that social networks have a substantial role to play in fostering this widening gulf. To be sure, educational systems have, to an admirable extent, closed the gap in access to educational resources, but many wealthy families have mobilized education as a vehicle (e.g. legacy admissions) to reproduce cultural, network and educational advantages (Bowles and Gintis, 1976).

In the end, a meritocratic system can only be partially meritocratic. If we delve deeper into the dynamics of a merit system, we see that inequalities of opportunities (i.e. unequal starting lines) are pervasive, and indeed, it is difficult, if not practically impossible, to ensure a level playing field. A meritocracy is purest in a hypothetical ‘first generation’ when everyone starts out equal, but once societies advance and families have accumulated wealth: certainly unevenly, then the mantra of equal opportunities can only be a myth. While meritocracies have helped many to climb out of their situations, they have also ensured that privileged children have pulled ahead

171 from the less fortunate by sizable amounts because of family resources (e.g. the child who gets to be educated overseas because the parents can afford it).

Next steps

An obvious next step in my analysis would be to ascertain the extent to which network inequalities account for wage inequalities between gender groups and ethnic groups, and this is what I intend to work on most immediately after the PhD. Some of my preliminary analyses show that some significant portion of ethnic inequalities in wages can be explained by ethnic differences in access to social capital, suggesting that ethnic inequalities in earnings cannot be attributed to education alone (as a meritocratic discourse would predict), but must evoke ethnic inequalities in social capital as well.

Limitations

This dissertation was not without limitations. The most general weakness is that the results are based upon cross-sectional data, rather than more ideally, longitudinal data. The issue of causality invariably crops up in situations like this. For example, in the first paper, is it work that generates social capital or social capital that generates work? Similarly, for the third paper, did accessed social capital come before the current job and therefore facilitated entry into it, or did it come only as a result of the current job?

Another limitation is the reliance on a single case study rather than more ideally, data from multiple source countries. It would have been ideal to have comparative data, but given the current circumstance, my partial solution was to position Singapore as an anchoring case and analyze and discuss it with reference to earlier research on countries such as the United States.

A third limitation is the reliance on name generator data, which according to a previous study (Marin, 2004) tends to elicit stronger ties rather than weaker ties. My study deals partially with this problem by incorporating a broad range of name generators (fourteen

172 altogether). That is, I cast a wide net over multiple social domains so that the extent of the strong-tie bias will not be so severe. Strong ties and name generators may be strongly correlated, but it is not name generators per se that cause strong ties. If the name generators deployed are widely-ranging, the elicited ties will likely include weak ties as well.

As these three limitations are design and budget limitations, they are not an actual indictment of the quality of the data itself. The data was collected by a professional research company, AC Nielsen, using a group of experienced mostly middle aged women trained to do interviews in the Singapore context. Logic checks were done by the company and verified by the Singapore university research team of which I was an instrumental part. Overall, the data was valuable and rich for advancing our theoretical understanding concerning the nature of social capital in a contemporary social context.

Final words

If there is a single take-home message in this dissertation, it would be that social capital does not exist in a vacuum, but is bound up with social contexts which substantially influence its distribution, role and value. These essays have suggested that investigations into social capital should move beyond a purely network approach, but deal with networks as being intertwined within larger aspects of social structure such as politics, economy, culture, education, ideology and society.

This dissertation has focused primarily on Singapore, but its broader theoretical relevance is that it highlights an instance of how larger socio-structural factors may often affect people’s experiences with social capital. Of course, given that each society is qualitatively different, the nature of the interplay between context and social capital will be different. That should not faze us. In my opinion, the future of social capital research is not with trying to come up with a grand theory of how social capital works, but more contextually, our aim should be to understand how diverse social environments give rise to correspondingly diverse experiences with social capital.

References

Bowles, Samuel and Herbert Gintis. 1976. Schooling in Capitalist America: Educational Reform and the Contradictions of Economic Life. New York: Basic Books.

Coleman, James S. 1988. “Social Capital in the Creation of Human Capital.” American Journal of Sociology 94:S95-S120.

Feld, Scott L. 1981. “The Focused Organization of Social Ties.” American Journal of Sociology 86:1015-1035.

Gamoran, Adam. 2001. “American Schooling and Educational Inequality: A Forecast for the 21 st Century.” Sociology of Education (Extra Issue):135-53.

Granovetter, Mark. 1985. “Economic Action, Social Structure, and Embeddedness.” American Journal of Sociology 83: 1420-1443.

Hall, Peter A. and David Soskice. 2001. Varieties of Capitalism: The Institutional Foundations of Comparative Advantage. Oxford: Oxford University Press.

Kao, Grace. 1995. “Asian Americans as Model Minorities? A Look at their Academic Performance.” American Journal of Education 103:121-59.

Lin, Nan. 2000. “Inequality in Social Capital.” Contemporary Sociology 29:785-95.

Marin, Alexandra. 2004. “Are Respondents More Likely to List Alters with Certain Characteristics?” Social Networks 26: 289-307.

McPherson, J. Miller, Lynn Smith-Lovin & Cook, J. M. 2001. “Birds of a Feather: Homophily in Social Networks .” Annual Review of Sociology 27: 415-444.

Swidler, Ann. 1986. “Culture in Action: Symbols and Strategies.” American Sociological Review 51: 273-286.

Tilly, Charles. 1998. Durable Inequality. Berkeley, CA: University of California Press.

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174

Uzzi, Brian. 1996. “The Sources and Consequences of Embeddedness for the Economic Performance of Organizations: The Network Effect.” American Journal of Sociology 61:674-698.

Young, Michael. 1958. Rise of the Meritocracy. London: Thames & Hudson.

Appendices

Appendix A -- List of name generators

1) Looking back over the past six months, who were the people with whom you discussed matters that are important to you?

2) You mentioned that you would ask someone you know to lend the money to you. Can you tell me who would this person be?

3) Suppose you feel just a bit down or depressed . And you wanted to talk to someone about it. Who could you turn to?

4) You mentioned that you came to know about this job through a friend/person. Can you tell me what is the name or initials of this friend/person?

5) You mentioned that someone in the company helped you get this job . Can you tell me what is the name or initials of this person?

6) Other than your spouse and you, who is your main childcare giver?

7) Can you give me the name or initials of the person whom you will ask or have asked to look after your house ?

8) Can you tell me the name or initials of the person who you get together with to discuss about hobbies or spare-time interests?

9) Thinking of the past six months, who were the two or three people with whom you spent the most time doing social activities with?

10) Can you please give me the name or initials of one of the army friends whom you still keep in contact with?

11) Can you tell me the name or initials of your most regular sports or exercise partner?

12) From among the people in these voluntary associations , who have you spoken to most recently?

13) Can you tell me the name or initials of important people whose names are currently missing from the list?

14) Do you know people who are from a different ethnic group as yours – people whom you could talk to, laugh with, have a good time?

175

176

Appendix B – Questionnaire Q’naire No : ______

English/ Chinese

Study ID 42161 (101-105) Resp. No. (106-109)

Interviewer No. (113-117) Interview Length (118-119)

No. Of Queries (120-121) Reference No. (122-126)

ACNielsen Research (Singapore) Pte Ltd 55 Newton Road #15-01 Revenue House Singapore 307987 Tel: 6252 8595

Feb 2005 (CCM)

Name: ______

Address: ______

______

Tel No: ______

Interviewer's Name: ______

Date of Interview: ______

Time Started/ Ended : ______to ______

Q1 RECORD POSTAL DISTRICT

(R1) Postal Code (127- 132)

Q2 RECORD FLOOR LEVEL

(R1) FLOOR LEVEL (133- 134)

177

SECTION A: DEMOGRAPHICS

Q3 ASK ALL Code Route SHOWCARD (135) May I know your age group?[SA]

请问你是属于哪个年龄组？ [SA]

19 years or below 1 CLOSE 20 - 24 years 2 CLOSE 25 - 29 years 3 Q4 30 - 34 years 4 Q4 35 - 39 years 5 Q4 40 - 44 years 6 Q4 45 - 49 years 7 Q4 50 - 55 years 8 Q4 56 years and above 9 CLOSE

Q4 RECORD GENDER [SA] Code Route (136) Male 1 Female 2

Q5 ASK ALL Code Route SHOWCARD (137) May I know what is your marital status? [SA]

请问你的婚姻状况是什么？[SA]

Single - currently attached 1 Single - currently not attached 2 Engaged 3 Married 4 Separated 5 Divorced 6 Widowed 7 Refused 8

Q6 ASK ALL Code Route Do you have any children? (include adopted children) [SA] (138)

你有没有孩子？(包括领养的孩子 )[SA]

Yes 1 Q7 No 2 Q8

178

Q7a ASK ALL WHO HAVE CHILDREN - CHECK Q6 CODE 1 Can you please tell me what is the age of your child/ children?

Interviewer : List from oldest to youngest.

可不可以告诉我你的孩子的年龄?

Q7a Record age of child (139-140) (R1) RECORD AGE OF CHILD 1: _ _ (141-142) (R2) RECORD AGE OF CHILD 2: _ _ (143-144) (R3) RECORD AGE OF CHILD 3: _ _ (145-146) (R4) RECORD AGE OF CHILD 4: _ _ (147-148) (R5) RECORD AGE OF CHILD 5: _ _ (149-150) (R6) RECORD AGE OF CHILD 6 : _ _ (151-152) (R7) RECORD AGE OF CHILD 7: _ _ (153-154) (R8) RECORD AGE OF CHILD 8: _ _ (155-156) (R9) RECORD AGE OF CHILD 9: _ _ (157-158) (R10) RECORD AGE OF CHILD 10: _ _

Q8 ASK ALL Code Route SHOWCARD (164) May I know what is your nationality? [SA]

请问你的国籍是什么？[SA]

Singapore Citizen 01 Q10 Citizen of China 02 Q9 Citizen of Hong Kong 03 Q9 Citizen of India 04 Q9 Citizen of Indonesia 05 Q9 Citizen of Malaysia 06 Q9 Cit izen of Taiwan 07 Q9

179

Q9 ASK ALL WHO ARE NOT SINGAPORE CITIZENS - CHECK Q8 CODES 2 or 6 Code Route Can you please tell me what is your current residency status in Singapore? [SA] (166)

请问你在新加坡目前的居留身份是什么？ [SA]

Permanent Resident (PR) 1 Dependent Pass Holder 2 Employment Pass Holder 3 Student Pass Holder 4 Social Visit Pass Holder 5 Work Permit Holder 6

Q10 RECORD ETHNIC GROUP [SA] Code Route (167) Chinese 01 Malay 02 Indian 03 Others (pls. specify) ______04

Q11 ASK ALL Code Route SHOWCARD (170) May I know what is your religion?[SA]

请问你信仰哪个宗教？ [SA]

Buddhism 01 Taoism/ Chinese traditional beliefs 02 Islam 03 Hinduism 04 Sikhism 05 Protestant 06 Roman Catholic 07 Free-thinker 08 Others (pls. specify) ______09 Christianity 10 Refused 20

180

Q12 ASK ALL Code Route Can you please tell me what is your housing type?[SA] (172)

请问你住在哪一类的房子？[SA]

HDB 1 to 2-room 01 HDB 3-room 02 HDB 4-room 03 HDB 5+-room 04 HDB Executive/ Mansionette 05 Executive Condominium/HUDC 06 Private Apartment/Condominium 07 Landed Property (Bungalow, Semi-Detached/ Terrace) 08 Shophouse 09 Others (pls. specify) ______10 Refused 11

Q13 ASK ALL Code Route Do you, or anyone else in your family living in this house or elsewhere, own this house?[SA] (174)

你或者住在这里或其它地方的家人是否拥有这所房子？[SA]

Yes, we own this house 01 Q14 No, we rent this house (i.e. we pay rent) 02 Q15 Others (pls. specify) ______03 Q15 Refused 10 Q15

Q14 ASK ALL WHO OWN THEIR HOUSE - CHECK Q13 CODE 1 Can you please tell me what is the PRESENT VALUE OF YOUR HOUSE ? By this, I mean the amount of money that this house will bring you if you sold it today. It does not matter if you do not know the exact value that this house is worth, we just need an estimation.

INSTRUCTION TO INTERVIEWER: If the respondent says 'Don't know/ Not sure/ Can't say', please record '99999 99999' in the space provided below.

If the respondents refuses to give an answer, please record '88888 88888' in the space provided below.

可不可以告诉我你的房子目前的价值多少？换句话说，如果你现在把这所房子卖掉，可以卖多少钱。如果你不知道这房子确实的价值也无所谓，我们只想知道大概的估计。

(R1) RECORD ESTIMATED PRESENT VALUE (175- OF HOUSE: S$ 216)

Q15 ASK ALL Code Route Does anyone in this household own a car? [SA] (222)

这房子有没有任何人拥有汽车？[SA]

Yes 1 No 2

181

Q16 ASK ALL Code Route Can you please tell me what is the highest level of education you have attained? [SA] (223)

请问你的最高学历是什么？[SA]

No formal education 01 Some Primary 02 Completed Primary (PSLE) 03 Some Secondary 04 Completed Secondary ('O'/ 'N' Levels) 05 ITE/ Vocational Institute 06 Completed Pre-U/ Junior College ('A' levels) 07 Polytechnic (Diploma) 08 Professional Qualifications/ Other Diplomas 09 University Graduate (Basic Degree/ Honors Degree) 10 University Postgraduate (MA, MSc, MBA, PhD, Graduate Diploma) 11 Refused 12

Q17 ASK ALL Code Route What is your current occupational status?[SA] (225) 你目前的就业情况是什么？[SA]

UNEMPLOYED: Unemployed - for more than one week but less than six months 01 Q19 Unemployed - for more than six months 02 Q19 Retired 03 Q19 Student 04 Q19 Housewife/ Home-maker 05 Q19 Student on school attachment 06 Q19 EMPLOYEE: Employed part-time 07 Q19 Employed full-time 08 Q19 SELF -EMPLOYED: Self-employed WITHOUT any business partners/ workers under me 09 Q19 Self-employed WITH business partners/ workers under me 10 Q18 Refused 11 Q19

Q18 ASK A LL WHO ARE SELF -EMPLOYED WITH BUSINESS PARTNERS/ WORKERS UNDER THEM - CHECK Q17 CODE 10 How many PAID EMPLOYEES do you have (excluding yourself)?

INSTRUCTION TO INTERVIEWER: If the respondent refuses to provide an answer, please record '999' in the space provided.

你有几位受薪的职员(不包括你自己)？

(R1) RECORD N O. OF PAID EMPLOYEES: (227- 229)

182

Q19 ASK ALL Code Route FOR THOSE WHO ARE CURRENTLY UNEMPLOYED : Can you please tell me what was your (235) last occupation?

FOR THOSE WHO ARE CURRENTLY EMPLOYED : Can you please tell me what is your present occupation?

INSTRUCTION TO INTERVIEWER: Please record the exact job designation mentioned: ______[SA]

FOR THOSE WHO ARE CURRENTLY UNEMPLOYED : 请问你最近的一份职业是什么？

FOR THOSE WHO ARE CURRENTLY EMPLOYED : 请问你目前的职业是什么？

Legislators, Senior Officials and Managers 01 Professional 02 Associate Professionals and Technicians 03 Clerical Workers 04 Service Workers and Shop and Market Sales Workers 05 Agricultural and Fishery Workers 06 Production Craftsmen and Related Workers 07 Plant and Machine Operators and Assemblers 08 Cleaners, Labourers and Related Workers 09 Others 10 Never worked before 11 Q22

183

Q20 ASK ALL WHO WORKS OR WORKED BEFORE CHECK Q19 CODE 1-10 Code Route FOR THOSE WHO ARE CURRENTLY UNEMPLOYED : Which industry did you work in (245) previously?

FOR THOSE WHO ARE CURRENTLY EMPLOYED : Which industry do you currently work in?

INSTRUCTION TO INTERVIEWER: Please record the exact industry description mentioned:

______[SA]

FOR THOSE WHO ARE CURRENTLY UNEMPLOYED : 请问你以前在哪个行业工作？

FOR THOSE WHO ARE CURRENTLY EMPLOYED : 请问你目前在哪个行业工作？ [SA]

Agriculture & Forestry 01 Fishing 02 Mining & Quarrying 03 Manufacturing 04 Electricity, Gas & Water 05 Construction 06 Wholesale & Retail Trade 07 Hotels & Restaurants 08 Transport, Storage & Communications 09 Financial Intermediation 10 Real Estate, Renting & Business Activities 11 Public Administration & Defence 12 Education 13 Health & Social Work 14 Other Community 15 Social & Personal Service Activities including repair of vehicles 16 Others (pls. specify) ______17 Domestic Work Activities 18 Refused 30

184

Q21 ASK AL L WHO WORKS OR WORKED BEFORE CHECK Q19 CODE 1 -10 Code Route (255) SHOWCARD FOR THOSE WHO ARE CURRENTLY UNEMPLOYED : Please look at this showcard and tell me which organization type does the company that you worked for previously, fall under.

FOR THOSE WHO ARE CURRENTLY EMPLOYED : Please look at this showcard and tell me which organization type does the company that you are currently working for, fall under. [SA]

FOR THOSE WHO ARE CURRENTLY UNEMPLOYED : 请看这张卡，然后告诉我你以前工作的那间公司属于哪种机构？

FOR THOSE WHO ARE CURRENTLY EMPLOYED : 请看这张卡，然后告诉我你目前工作的那间公司属于哪种机构？[SA]

Singapore-owned private firm 01 Government-linked corporation 02 Multi-national corporation 03 Statutory board 04 Civil service/ Military 05 Non-profit organization 06 Overseas Company 07 Don't know/ Not sure/ Can't say/ Can't remember 19 Refused 20

185

Q22 ASK ALL Code Route SHOWCARD (257) On average, how much do the people in your household earn altogether in a month? 你全家人每个月的平均总收入是多少？ [SA]

No income 01 Below S$750 02 S$751 - 1,000 03 S$1,001 - 1,500 04 S$1,501 - 2,000 05 S$2,001 - 2,500 06 S$2,501 - 3,000 07 S$3,001 - 3,500 08 S$3,501 - 4,000 09 S$4,001 - 5,000 10 S$5,001 - 6,000 11 S$6,001 - 7,000 12 S$7,001 - 8,000 13 S$8,001 - 9,000 14 S$9,001 - 10,000 15 S$10,001 - 11,000 16 S$11,001 - 12,000 17 S$12,001 - 13,000 18 S$13,001 - 14,000 19 S$14,001 - 15,000 20 Above S$15,000 21 Don't know/ Not sure/ Can't say/ Can't remember 22 Refused 23

186

Q23 ASK ALL WHO WORKS OR WORKED BEFORE CHECK Q19 CODE 1-10 Code Route (260) SHOWCARD FOR THOSE WHO ARE CURRENTLY UNEMPLOYED : Can you please tell me on average, how much did you yourself earn in a month previously?

FOR THOSE WHO ARE CURRENTLY EMPLOYED : Can you please tell me on average, how much do you yourself currently earn in a month?[SA]

FOR THOSE WHO ARE CURRENTLY UNEMPLOYED : 请问你以前每个月的平均收入是多少？

FOR THOSE WHO ARE CURRENTLY EMPLOYED : 请问你目前每个月的平均收入是多少？ [SA]

No income 01 Below S$500 02 S$501 - 750 03 S$751 - 1,000 04 S$1,001 - 1,500 05 S$1,501 - 2,000 06 S$2,001 - 2,500 07 S$2,501 - 3,000 08 S$3,001 - 3,500 09 S$3,501 - 4,000 10 S$4,001 - 5,000 11 S$5,001 - 6,000 12 S$6,001 - 7,000 13 S$7,001 - 8,000 14 S$8,001 - 9,000 15 S$9,001 - 10,000 16 Above S$10,000 17 Can't remember 18 Refused 19

187

SECTION B: LIFE SITUATIONS AND EVENTS

Q24 ASK ALL Code Route SHOWCARD (262) Now, I would like you to give me a rough idea of some of the things that have taken place in your life over the past one year.

Please take a look at the items listed on this showcard and tell me if any of these things have happened to you or any person in your household in the past one year.

INSTRUCTION TO INTERVIEWER: If the respondent selects Code 31, he/ she is not allowed to select any other responses.

现在，我想大概知道在过去一年内，你生活中发生的一些事物？

请看这张卡上列出的事项，请问你或你家里任何人在过去一年内有没有经历过这里的任何事件？ [MA]

JOB/ MAKING A LIVING: Got a new job 01 Got a promotion or pay raise at work 02 Got retrenched or lost a job 03 Searched for a new job 04 Experienced problems with own business 05 Experienced financial problems 06 Experienced employment discrimination 07 NEW EXPERIENCES: Got married/ engaged 08 Found a new close friend 09 Found a new hobby or sport 10 Found a new religious experience 11 Went for a holiday outside of Singapore 12 Bought a new car 13 Became pregnant/ Had a baby 14 Issues related to child/ children's schooling needs (e.g. needed to find a school for child etc.) 15 HOUSE MAINTENANCE: Moved house 16 Tried to move house or buy a home 17 Needed help to carry heavy furniture 18 Had broken/ spoilt appliances 19 Needed home repairs or renovations 20 Experienced problems with a neighbour 21 Did not have enough help with housework 22 DIFFICULT TIMES: Experienced serious illnesses or health problems/ injuries 23 Experienced the death of a family member/ friend 24 Was a victim of crime 25 Experienced serious relationship problems (boyfriend/ girlfriend, spouse) 26 Experienced difficulties at school (e.g. with people, grades etc.) 27 Was 'played out' by others (e.g. sabotaged etc.) 28 Lost something precious (e.g. handphone etc.) 29 Experienced difficulties at work (e.g. being scolded by boss, engulfed by office politics etc.) 30

188

Q24 ASK ALL Code Route SHOWCARD (262) Now, I would like you to give me a rough idea of some of the things that have taken place in your life over the past one year.

Please take a look at the items listed on this showcard and tell me if any of these things have happened to you or any person in your household in the past one year.

INSTRUCTION TO INTERVIEWER: If the respondent selects Code 31, he/ she is not allowed to select any other responses.

现在，我想大概知道在过去一年内，你生活中发生的一些事物？

请看这张卡上列出的事项，请问你或你家里任何人在过去一年内有没有经历过这里的任何事件？ [MA]

NONE OF THE ABOVE 31 Q26

Q25 ASK ALL WHO GAVE A RESPONSE IN Q24 - SELECTED ANY RESPONSE BETWEEN Code Route CODES 1 TO 30 (266) When these things happened [READ OPTIONS SELECTED IN Q24] , did you discuss them with anyone? [SA]

当你[READ OPTIONS SELECTED IN Q24] 的时候，你有没有跟任何人谈论过这事情？ [SA]

Yes 1 No 2

INSTRUCTION TO INTERVIEWER: Please read the following text to the respondent

Now, I will ask you about some of the people in your life. Depending on the question asked, they may include your relative, boss, co-worker, neighbor, friend, or even an acquaintance. Please provide me with their names or initials. Let's start with a general question.

我们想了解你生活中的一些人物。根据个别的问题，他们有可能包括你的亲戚、老板、同事、邻居、朋友或者只是认识的人。请告诉我他们的名字或简称。我们先问一个基本的问题。

Q26 ASK ALL From time to time, most people DISCUSS IMPORTANT MATTERS with others, and what these IMPORTANT MATTERS are, differ and vary from one person to another. It can be about anything - your job situation, new experiences, happenings in the family, relationships etc.; as long as it is something that is IMPORTANT to you.

If you look back at the past six months, who were the people with whom you DISCUSSED MATTERS THAT ARE IMPORTANT TO YOU ?. Please provide me with two names.

多数人会时不时跟别人谈论重要的事情。至于重要的事情是什么，每个人的看法各有不同。它可以是任何事情，包括你的工作、新的体验、家里发生的事情、人际关系等等，只要是你自己觉得重要的事情。

请回想过去的6个月，你曾跟哪些人谈论过你觉得重要的事情？请告诉我两个名字。

(R1) RECORD NAME/ INITIALS OF PERSON 1: ______

189

If you look back at the past six months, who were the people with whom you DISCUSSED MATTERS THAT ARE IMPORTANT TO YOU ?. Please provide me with two names.

请回想过去的6个月，你曾跟哪些人谈论过你觉得重要的事情？请告诉我两个名字。

(267-268)

(R2) RECORD NAME/ INITIALS OF PERSON 2: ______

(269-270)

190

Q27 ASK ALL Code Route In the course of living, some people run into financial problems while others are lucky enough not (271) to. Now, let's assume that you need to get a large sum of money together to save your business or to repay some debts. What would you do? Would you... [READ LIST] ? [SA] 在生活中，有些人会不幸遇到经济问题。现在，假设你需要一大笔钱来援助你的生意或偿还一些债务。请问你会怎么做？你会不会... [READ LIST] ?

Ask someone you know to lend it to you 1 Q28 找你认识的人借钱给你 Go to a bank or credit union to get a loan 2 Q29 到银行或信贷机构去贷款 Ask someone you know to lend it to you AND go to a bank or credit union to get a loan 3 Q28 找你认识的人借钱给你，也到银行或信贷机构去贷款 Do something else 4 Q29 做其它的事情

Q28 ASK AL L WHO WILL ASK SOMEONE THEY KNOW TO LEND MONEY TO THEM - CHECK Q27 CODES 1 OR 3 You mentioned that you would ask someone you know to lend the money to you. Can you please tell me who would this person be? 你说你会跟你认识的人借钱。请问你会跟谁借呢？

(R1) RECORD NAME/ I NITIALS OF PERSON 3: ______

(272-273)

Q29 ASK ALL(SKIP TO Q30 IF IMMEDIA TE FAMILY WAS MENTIONED IN Q28 Code Route Let's just say that you face a financial crisis of some kind one day. Do you think your (274) IMMEDIATE FAMILY would be willing to help you out? [SA]

假如说有一天你遇到经济困难。你认为你的家人会不会愿意帮助你？[SA]

Yes 1 No 2 Don't know/ Not sure/ Can't say 3

Q30 ASK ALL (SKIP TO Q31 IF RELATIVES WERE MENTIONED IN Q28 Code Route What about any of your RELATIVES ? Do you think they will be willing to help you out? (275) 那么你任何的亲戚呢？你认为他们会不会愿意帮助你呢？[SA]

Yes 1 No 2 Don't know/ Not sure/ Can't say 3 Some relatives will help while others will not 4 I don't have any relatives 5

Q31 ASK ALL Code Route Did you borrow a large amount of money from someone over the past 12 months? [SA] (276) 你在过去12 个月内有没有跟人借过一大笔钱？[SA]

Yes 1 No 2

191

SECTION C: MENTAL STATE AND WELL -BEING

Q32 ASK ALL DROPCARD We have talked about life events, situations and circumstances so far. Now, let's talk about how you have been FEELING over the PAST ONE WEEK .

For each of the following statements, please select a score between 1 to 4, that best describes HOW OFTEN you felt this way DURING THE PAST ONE WEEK . [SA]

我们谈过了生活中发生的事、状况和机遇。现在，我们谈谈你在过去一个星期内的心情感觉。

针对以下各个句子，请从1到4之中选一个号码来说明你在过去一个星期内多常有这种感觉。 [SA]

Rarely or Some or a Occasionall Most or all none of the little of the y or a of the time time (< 1 time (1 - 2 moderate (5 - 7 days) day) days) amount of time (3 - 4 During the past week ……. days) (277) (R1) I was bothered by things that usually don't bother me 1 2 3 4 (278) (R2) I had trouble keeping my mind on what I was doing 1 2 3 4 (279) (R3) I felt depressed 1 2 3 4 (280) (R4) I felt like everything I did was an effort 1 2 3 4 (313) (R5) I felt hopeful about the future 1 2 3 4 (314) (R6) I felt fearful 1 2 3 4 (315) (R7) My sleep was restless 1 2 3 4 (316) (R8) I was happy 1 2 3 4 (317) (R9) I felt lonely 1 2 3 4 (318) (R10) I felt tired and could not get going 1 2 3 4

192

Q33 ASK ALL Now, suppose you feel just a bit down or depressed. And you wanted to talk to someone about it. Who could you turn to?

现在，假设你感到有点消沉或抑郁，而且你想向别人倾诉。你可以向谁倾诉？

(R1) RECORD NAME/ INITI ALS OF PERSON 4: ______

(319-320)

(R2) RECORD NAME/ INITIALS OF PERS ON 5: ______

(321-322)

Q34 ASK ALL Code Route Generally speaking, how would you feel if you had to go for some form of counseling to deal with (323) a personal problem? Would you be... [READ LIST] ? [SA]

一般而言，如果你需要寻求某些形式的辅导来解决一些个人的问题，你会感觉如何？你会不会... [R EAD LIST] ?[SA]

Very ashamed to let others know 1 很羞于让人知道 Ashamed to let others know 2 羞于让人知道 A bit ashamed to let others know 3 有一点羞于让人知道 Not ashamed at all to let others know 4 完全不会羞于让人知道

Q35 ASK ALL Code Route Can you please tell me if you have gone for some form of formal counseling over the past 12 (324) months?[SA]

请问你在过去12个月内有没有去寻求过专业的辅导？[SA]

Yes 1 No 2

193

INSTRUCTION TO INTERVIEWER: Please read out the following text to the respondent:

So far, we have talked about your general life situation, some of your present day feelings as well as your well-being as a whole. Now, let's focus on more specific areas of your life. Let's start with your WORK .

我们已经谈过了你一般的生活、你最近的心情和你整体的状况。现在，我们专注谈你生活中的各方面。就从你的工作开始吧。

Q36 ASK ALL WHO ARE CURRENTLY EMPLOYED - CHECK Q17 CODES 6 - 10 Code Route Generally speaking, how much would you say you like your present job? Do you... [READ (325) LIST] ? [SA] 一般而言，你有多喜欢你目前的工作？你是不是... [READ LIST] ?[SA]

Don't like it at all 1 完全不喜欢 Don't like it 2 不喜欢 Like it 3 喜欢 Like it very much 4 非常喜欢

Q37 ASK ALL WHO ARE CURRENTLY EMPLOYED - CHECK Q17 CODES 6 - 10 Code Route How satisfied would you say you are with your current salary? Are you... [READ LIST] ?[SA] (326) 你对你目前的薪金有多满意？你是不是... [READ LIST] ?[SA]

Not satisfied at all 1 完全不满意 Not satisfied 2 不满意 Quite satisfied 3 相当满意 Very satisfied 4 很满意

Q38 ASK ALL WHO ARE CURRENTLY UNEMPLOYED - CHECK Q17 CODE 2 Code Route How long have you been unemployed/ stop working? [SA] (327) 你没有受雇/停止工作已经多久了？[SA]

Less than 6 months 1 不到6个月 6 months to 1 year 2 6个月到1年内 1 - 3 years 3 1 – 3 年 4 - 6 years 4 4 – 6 年 7 - 9 years 5 7 – 9 年 10 - 15 years 6 10 – 15 年 More than 15years 7 超过15 年

194

Q39 ASK ALL Code Route SHOWCARD (328) FOR THOSE WHO ARE CURRENTLY UNEMPLOYED : Looking at this showcard, can you please tell me how did you get hired for your last job?

FOR THOSE WHO ARE CURRENTLY EMPLOYED : Looking at this showcard, can you please tell me how did you get hired for your current job? [SA]

FOR THOSE WHO ARE CURRENTLY UNEMPLOYED : 请看这张卡，请问你最近那份工作是如何找到的？

FOR THOSE WHO ARE CURRENTLY EMPLOYED : 请看这张卡，请问你目前这份工作是如何找到的？ [SA] I was HIRED from outside the organization 01 I was TRANSFERRED from another division within the organization 02 I was PROMOTED from another position within the same division 03 I started MY OWN BUSINESS 04 Q50 Never worked before 05 Q61 Others (pls. specify) ______06 Family business 07 Serve National Service 08 Bonded 09 Can’t remember 19 Refused 20

Q40 ASK ALL WHO HAVE WORKED BEFORE - CHECK Q39 CODE 1 -3, 6 -9, 19 -20 Code Route How did you come to know about this job? (331) 你是从哪里知道有这份工作的？[MA]

If respondent has few positions with the same company, ask his or her 'first' position with the company[MA]

I saw an ADVERTISEMENT in a newspaper (magazine, trade, technical journal etc.) 01 Q42 I found out through an EMPLOYMENT AGENCY (or personnel consultant, head-hunter etc.) 02 Q42

I SUBMITTED AN APPLICATION before anyone told me about the job 03 Q42 Someone I didn't know contacted me and said that I had been RECOMMENDED 04 Q42 I asked a FRIEND / PERSON who told me about the job 05 Q41 A FRIEND / PERSON who knew I was looking for a job contacted me 06 Q41 A FRIEND / PERSON who didn't know I was looking for a job contacted me 07 Q41 Others (pls. specify) ______08 Q42 Family business 09 Q41 Signed on after National Service 10 Q44 Bonded 11 Q44 Not sure/ Can't say/ Can't remember 19 Q42 Refused 20 Q42

195

Q41 ASK ALL WHO FIRST CAME TO KNOW ABOUT THE JOB VIA A FRIEND/ PERSON - CHECK Q40 CODES 5 – 7 & 9 You mentioned that you came to know about this job through a friend/ person. Can you please tell me what is the name or initials of this friend/ person? INSTRUCTION TO INTERVIEWER: Please record the name or initials of this friend/ person

你说你是通过一个朋友/人知道这份工作的。可不可以告诉我这个朋友/人的名字或简称？

(R1) RECORD NAME/ INITIALS OF PERSON 6: (333-334)

Q42 ASK ALL WHO HAVE WORKED BEFORE - CHECK Q39 CODE 1 -3, 6 -7, 19 -20 Code Route Was there someone IN THE COMPANY WHO HELPED YOU get this job? [SA] (335)

是不是这间公司里有人帮助你获得这份工作？ [SA]

Yes 1 Q43 No 2 Q44

Q43 ASK ALL WHO MENTIONED THERE WAS SOMEONE IN THE COMPANY WHO HELPED THEM GET THE JOB - CHECK Q42 CODE 1 You mentioned that someone in the company helped you get this job. Can you please tell me what is the name or initials of this person?

INSTRUCTION TO INTERVIEWER: Please record the name or initials of this person.

你说是公司里有人帮助你获得这份工作。可不可以告诉我这个人的名字或简称？

(R1) RECORD NAME/ INITIALS OF PERSON 7: ______

(336-337)

Q44 ASK ALL WHO ARE CURRENTLY EMPLOYED CHECK Q17 CODE 6 -10 And for how long have you been in the company?

那么你在这间公司有多久了？

(R1) RECORD N O. OF YEARS RESPONDENT HAS BEEN IN COMPANY: (338- 339)

Q45 ASK ALL WHO ARE CURRENTLY EMPLOYED - CHECK Q17 CODES 6 - 10 Code Route Of your colleagues at work, has there been anybody who has been QUITE DIFFICULT TO GET (345) ALONG WITH ?[SA]

你工作的同事当中，有没有任何人是相当难相处的？[SA]

Yes 1 Q46 No 2 Q49

196

Q46 ASK ALL WHO HAS A COLLEAGUE WHO HAS BEEN QUITE DIFFICULT TO GET ALONG Code Route WITH - CHECK Q45 CODE 1 (346) How is he/ she related to you? Is he/ she your... [READ LIST] ? [SA]

他跟你是什么关系？他是不是你的... [READ LIST] ?[SA]

Boss/ Manager/ Supervisor 1 老板/经理/上司 Co-worker 2 同阶层的同事 Subordinate 3 下属 Just someone else at work 4 只是工作上的某一个人

Q47 ASK ALL WHO HAS A COLLEAGUE WHO HAS BEEN QUITE DIFFICULT TO GET ALONG WITH - CHECK Q4 5 CODE 1 How long has this person been in the company?

INSTRUCTION TO INTERVIEWER: If the respondent says 'Don't know/ Not sure/ Can't say/ Can't remember', please record '99' in the space provided below.

这个人在这间公司有多久了？

(R1) RECORD N O. OF YEARS PERSO N HAS BEEN IN COMPANY: (347- 348)

Q48 ASK ALL WHO HAS A COLLEAGUE WHO HAS BEEN QUITE DIFFICULT TO GET ALONG Code Route WITH - CHECK Q45 CODE 1 (354) Between this person and you, who would you say is more knowledgeable in your area of work? [SA]

你觉得在你的工作方面，你和这个人之间谁懂得比较多？ [SA]

Me 1 Him/ Her 2 Same 3 Don’t know 4

Q49 ASK ALL WHO ARE CURRENTLY EMPLOYED - CHECK Q17 CODES 6 - 10 Code Route In your opinion, how easy would it be for you to find a job with another employer that provides (355) approximately the same income and fringe benefits as what you have now? Would you say it is... [READ LIST] ? [SA]

在你看来，你如果要找跟你现在大概一样薪金和福利的另一份工作，这有多容易？你会说这是... [READ LIST] ?[SA]

Not easy at all 1 根本不容易 Not easy 2 不容易 Somewhat easy 3 算是容易 Very easy 4 非常容易

197

SECTION D: WORKPLACE CENSUS

INSTRUCTION TO INTERVIEWER: Please read out the following text:

Now, I am going to collect some information about the people whom you work with.

现在，我想知道跟你一起工作的人的资料。

Q50 ASK ALL WHO ARE CURRENTLY EMPLOYE D - CHECK Q17 CODES 6 - 10 Code Route Do you WORK DIRECTLY with anyone?[SA] (356)

你的工作是否跟任何人有直接的接触？ [SA]

Yes 1 Q51 No 2 Q61

Q51 ASK ALL WHO WORK DIRECTLY WITH SOMEONE - CHECK Q50 CODE 1 Code Route Do you SUPERVISE the work of others or tell other employees what work they should do?[SA] (357)

你是否监督其他人的工作或指示其他雇员他们应该做些什么？ [SA]

Yes 1 No 2

Q52 ASK ALL WHO WORK DIRECTLY WITH SOMEONE - CHECK Q50 CODE 1 How many people are there in your WORK GROUP (DEPARTMENT) in total?

你的工作组(部门)总共有几个人？

(R1) RECORD NO. OF PEOPLE IN WORK GROUP/ DEPARTMENT: (358- 360)

Q53 ASK ALL WHO WORK DIRECTLY WITH SOMEONE - CHECK Q50 CODE 1 How many CO-WORKERS do you need to deal with on a DAILY BASIS ON AVERAGE?

你在工作上每天通常需要跟几个同事一起做事？

(R1) RECORD NO. OF CO -WO RKERS DEAL WITH ON DAILY BASIS: (366- 368)

198

Q54 ASK ALL WHO WORK DIRECTLY WITH SOMEONE - CHECK Q50 CODE 1 Can you please tell me how many of these co-workers of yours do you deal with on a daily basis on average, fit the profile of being a ... [READ LIST]?

INSTRUCTION TO INTERVIEWER: Please read the following options: 1. Singapore Chinese. 2. Singapore Malay. 3. Singapore Indian. 4. Chinese National. 5. Indian National. 6. Members of other ethnicity/ nationality.

R1 to R6 should add up to Q53

请告诉我你在日常工作接触的同事当中有几位是... [READ LIST] ?

INSTRUCTION TO INTERVIEWER: Please read the following options: 1. 新加坡的华人 2. 新加坡的马来人 3. 新加坡的印度人 4. 中国国籍的人 5. 印度国籍的人 6. 其他种族/国籍的人

(R1) RECORD NO. OF SINGAPORE CHINESE: (374- 376) (R2) RECORD NO. OF SINGAPORE MAL AYS: (377- 379) (R3) RECORD NO. OF SING AP ORE INDIANS: (380- 414) (R4) RECORD NO. OF CHINESE NATIONALS: (415- 417) (R5) RECORD NO. OF INDIAN NATIONALS: (418- 420) (R6) RECORD NO. OF PEOPLE OF OTHER ETHNICITY/ NATIONALITY: (421- 423)

Q55 ASK ALL WHO GAVE A RESPONSE TO R1 IN Q54 Can you please tell me how many of these SINGAPORE CHINESE are Males? And how many of them are Females?

R1 + R2 should add up to R1 in Q54

请问这些新加坡华人当中，有几位是男性？那么有几位是女性？

(R1) RECORD NO. OF MALES: (429- 431) (R2) RECORD NO. OF FEMALES: (432- 434)

199

Q56 ASK ALL WHO GAVE A RESPONSE TO R2 IN Q54 Can you please tell me how many of these SINGAPORE MALAYS are Males? And how many of them are Females?

R1 + R2 should add up to R2 in Q54

请问这些新加坡马来人当中，有几位是男性？那么有几位是女性？

(R1) RECORD NO. OF MALES: (440- 442) (R2) RECORD NO. OF FEMALES: (443- 445)

Q57 ASK ALL WHO GAVE A RESPONSE TO R3 IN Q54 Can you please tell me how many of these SINGAPORE INDIANS are Males? And how many of them are Females?

R1 + R2 should add up to R3 in Q54

请问这些新加坡印度人当中，有几位是男性？那么有几位是女性？

(R1) RECORD NO. OF MALES: (451- 453) (R2) RECORD NO. OF FEMALES: (454- 456)

Q58 ASK ALL WHO GAVE A RESPONSE TO R4 IN Q54 Can you please tell me how many of these CHINESE NATIONALS are Males? And how many of them are Females?

R1 + R2 should add up to R4 in Q54

请问这些中国人当中，有几位是男性？那么有几位是女性？

(R1) RECORD NO. OF MALES: (462- 464) (R2) RECORD NO. OF FEMALES: (465- 467)

Q59 ASK ALL WHO GAVE A RESPONSE TO R5 IN Q54 Can you please tell me how many of these INDIAN NATIONALS are Males? And how many of them are Females?

R1 + R2 should add up to R5 in Q54

请问这些印度人当中，有几位是男性？那么有几位是女性？

(R1) RECORD NO. OF MALES: (473- 475) (R2) RECORD NO. OF FEMALES: (476- 478)

Q60 ASK ALL WHO GAVE A RESPONSE TO R6 IN Q54 Can you please tell me how many of these members of other ethnicity/ nationality are Males? And how many of them are Females?

R1 + R2 should add up to R6 in Q54

请问这些其他种族/国籍的人当中，有几位是男性？那么有几位是女性？

(R1) RECORD NO. OF MALES: (516- 518)

200

Q60 ASK ALL WHO GAVE A RESPONSE TO R6 IN Q54 Can you please tell me how many of these members of other ethnicity/ nationality are Males? And how many of them are Females?

R1 + R2 should add up to R6 in Q54

请问这些其他种族/国籍的人当中，有几位是男性？那么有几位是女性？

(R2) RECORD NO. OF FEMALES: (519- 521)

201

INSTRUCTION TO INTERVIEWER: Please read the following text to the respondent: We have talked about your work place. Now, let's move on and talk about your FAMILY LIFE . 我们已经谈过了你的工作。现在，我们谈谈你的家庭生活。

Q61a ASK ALL First of all, I would like to collect some information about your IMMEDIATE AND EXTENDED FAMILY .

Can you please tell me how many of each of the following types of relatives do you currently have? By that, I mean those relatives whom are alive. (INTERVIEWERS: PLEASE READ TYPES OF RELATIVES. FOR AUNTS/UNCLES/COUSINS DO NOT NEED TO ASK FOR TOTAL NUMBER. AUNT/UNCLES ARE DEFINED AS 'SIBILINGS OF PARENTS)

首先，我想知道你的直属家人和远亲的资料。可不可以告诉我你目前有几位以下的各种亲戚？我指的是，还在世的那些亲戚。

Q61b And can you please tell me if any of your ______[READ TYPE OF RELATIVES RESPONDENT GAVE A RESPONSE FOR IN Q61a] LIVE IN THE SAME HOUSE as you? [SA]

那么，请问你的任何______[READ TYPE OF RELATIVE RESPONDENT GAVE A RESPONSE FOR IN Q61a] 有没有跟你住在一起？ [SA]

Q61c Do any of them LIVE IN THE SAME NEIGHBOURHOOD (i.e. within a 10 -minute walk)?[SA] 他们有没有任何人住在同一个邻里区呢(就是走路10 分钟内可以到)？ [SA]

Q61d Do any of them LIVE OUTSIDE SINGAPORE ? [SA] 他们有没有任何人是住在国外的？[SA]

Q61a Q61b Q61c Q61d Record no. Yes No Yes No Yes No of relatives (527-528) (547) (557) (567) (R1) RECORD NO. OF PARENTS: _ _ 1 2 1 2 1 2 (529-530) (548) (558) (568) (R2) RECORD NO. OF BROTHERS: _ _ 1 2 1 2 1 2 (531-532) (549) (559) (569) (R3) RECORD NO. OF SISTERS: _ _ 1 2 1 2 1 2 (533-534) (550) (560) (570) (R4) RECORD NO. OF SONS: _ _ 1 2 1 2 1 2 (535-536) (551) (561) (571) (R5) RECORD NO. OF DAUGHTERS: _ _ 1 2 1 2 1 2 (537-538) (552) (562) (572) (R6) REC ORD NO. OF GRANDPARENTS: _ _ 1 2 1 2 1 2 (539-540) (553) (563) (573) (R7) RECORD NO. OF PARENTS -IN -LAW: _ _ 1 2 1 2 1 2 (554) (564) (574)

(R8) RECORD NO. OF AUNTS: 1 2 1 2 1 2 (555) (565) (575) (R9) RECORD NO. OF UNCLES: 1 2 1 2 1 2 (556) (566) (576) (R10) RECORD NO. OF COUSINS: 1 2 1 2 1 2

202

INSTRUCTION TO INTERVIEWER: Please read the following text to the respondent:

The following questions are with regards to the things pertaining to FAMILY MAINTENANCE and YOUR CHILDREN (IF ANY) .

接下来的问题是有关维持家庭和有关你的孩子。

Q62 ASK ALL Code Route Does your household employ a maid? (614)

INSTRUCTION TO INTERVIEWER: If the respondent is MARRIED and selects Code 2 here, please proceed to Q64. If the respondent is SINGLE/ ENGAGED/ SEPARATED/ DIVORCED/ WIDOWED/ REFUSED and selects Code 2 here, please proceed to Q65 . [SA]

你的家有没有聘请女佣？ [SA]

Yes 1 Q63 No 2 Q64

Q63 ASK ALL WHOSE HOUSEHOLD EMPLOYS A MAID - CHECK Q62 CODE 1 Code Route Generally speaking, how much housework does the maid in your household do? [SA] (615)

一般来说，你家的女佣需要做多少工作？ [SA]

All of it 01 Most of it, someone in the household helps along with some tasks (e.g. cooking etc.) 02 Just some of it, someone in the household does the bulk of it 03 Others (pls. specify) ______04 Don't know/ Not sure/ Can't say 20

Q64 ASK ALL WHO ARE MARRIED - CHECK Q5 CODE 4 Code Route Does your spouse work?[SA] (617)

你的妻子/丈夫有没有工作？[SA]

Yes 1 No 2

203

Q65 ASK ALL WHO HAVE CHILD/ CHILDREN - CHECK Q6 CO DE 1 Code Route Other than your spouse or you, who else takes care of your child/ children? For example, when (618) both your spouse and you work? [SA]

除了你的配偶和你之外，还有谁照顾你的孩子？例如，当你和妻子/丈夫都在工作的时候？ [SA]

Nobody, our child/ the children are old enough to take care of themselves 01 We take them with us to work 02 Another relative who lives in the same house 03 Another relative who lives in a different house 04 The maid 05 A neighbour 06 A childcare organization 07 A tuition centre/ school 08 This situation does not apply to me/ has not happened to me yet 09 Others (pls. specify) ______10 Don't know/ Not sure/ Can't say 30

Q66 ASK ALL WHO HAVE CHILD/ CHILDREN - CHECK Q6 CODE 1 Code Route What about when your spouse and you have to leave the house for a few hours (e.g. shopping (621) etc.)?[SA]

那么，当你和妻子/丈夫需要离开家里几个小时的的时候呢(例如去购物)？[SA]

Nobody, our child/ the children are old enough to take care of themselves 01 We take them along with us 02 Another relative who lives in the same house 03 Another relative who lives in a different house 04 The maid 05 A neighbour 06 A childcare organization 07 A tuition centre/ school 08 This situation does not apply/ has not happened to me yet 09 Others (pls. specify) ______10 Don't know/ Not sure/ Can't say 30

Q67 ASK ALL WHO HAVE CHILD/ CHILDREN - CHECK Q6 CODE 1 Other than your spouse and you, who is your main childcare giver?

INSTRUCTION TO INTERVIEWER: Please ensure that the response that appears here, appears in either Q65 or Q66.

除了你的配偶和你之外，谁是主要看顾你的孩子？

(R1) RECORD NAME/INITIALS OF PERSON 8 ______

(624-625)

204

Q68 ASK ALL Code Route Have you ever provided child care for someone else? [SA] (642)

你是否曾经给别人看顾孩子？ [SA]

Yes 1 Q69 No 2 Q70

Q69 ASK ALL WHO PROVIDE CHILD CARE FOR SOMEONE ELS E - CHECK Q68 CODE 1 Code Route When was the last time you provided such child care? [SA] (643)

你最近一次给别人看顾孩子是什么时候？ [SA]

Within the last two days 1 Within the last week 2 Within the last month 3 Within the last six months 4 Longer ago than that 5

Q70 ASK ALL Code Route When people go out of Singapore for a while, they sometimes ask someone to TAKE CARE OF (644) THEIR HOUSE for them, for example, to water the plants, pick up the mail, feed a pet, bring in the newspapers or simply just to check on things.

If you and your family went out of Singapore for a while, such that the whole house is empty, would you ask someone to take care of your house for you in any of the above-mentioned ways while you are away? [SA]

有些人出国的时候，他们会叫别人帮忙照顾他们的家，例如浇花、收信件、喂宠物、收报纸或者只是检查家里有没有问题。

如果你和全家人出国一阵子，整个家里没有人的话，你会不会请别人在你不在家的时候帮你照顾你的家呢？例如以上那些方式。 [SA]

Yes 1 Q71 No 2 Q72

Q71 ASK ALL WHO MENTIONED THEY WILL GET SOMEONE TO LOOK AFTER THEIR HOUSE - CHECK Q70 CODE 1 Can you give me the name or initials of the person whom you will ask or have asked to look after your house? Kindly note that the person that you name, must not be anyone who is currently living in the same house as you.

请问你会找谁照顾你的家，可不可以告诉我他的名字或简称？不过，你提到的这个人不应该是目前跟你住在同一个屋子的人。

(R1) RECORD NAME/ INITIALS OF PERSON 9: ______

(645-646)

205

INSTRUCTION TO INTERVIEWER: Please read the following text to the respondent:

So far, we have talked about your general life situation, your work place and your family. Now, let us talk about about some informal aspects of socializing, including what you enjoy doing during your free time and with whom you spend your free time etc.

我们已经谈过了你一般的生活状况、你的工作和你的家庭。现在，我们来谈谈你较随兴的社交生活，包括了你喜欢在休闲时间做些什么及你和谁度过你的消闲时间。

Q72 ASK ALL Code Route Sometimes, people get together with others to DISCUSS ABOUT HOBBIES OR SPARE-TIME (647) INTERESTS THEY HAVE IN COMMON . Do you ever do this with anyone? [SA]

有的时候，人家喜欢聚在一起谈他们共同的嗜好或休闲的兴趣。你有没有跟别人一起这样做呢？ [SA]

Yes, discuss with someone 1 Q73 No, never discuss with anyone 2 Q74 I do not have any hobbies or spare-time interests 3 Q74

Q73 ASK ALL WHO GET TOGETHER WITH OTHERS - CHECK Q72 CODE 1 Can you please tell me the name or initials of the person whom you get together with to discuss about hobbies or spare-time interests?

请问你会跟谁在一起谈嗜好或休闲的兴趣呢？可不可以告诉我他的名字或简称？

(R1) RECORD NAME/ INITIALS OF PERSON 1 0: ______

(648-649)

206

Q74 ASK ALL Thinking of the past six months, who were the two or three people with whom you spent the most time DOING SOCIAL ACTIVITIES with? Such as going out for drinks, watching a movie, window shopping, going for meals, playing mahjong, drinking with a group of friends, meeting friends at coffee shop for a chat, family 'get together' etc. Can you please give me the names or initials of two persons?

在过去6个月内，你最常跟哪两三个人一起进行社交活动呢？例如出去喝饮料、看电影、逛街、去吃饭、打麻将、跟一群朋友喝东西、在咖啡店跟朋友见面聊天、家人相聚等。可不可以告诉我两个人的名字或简称？

(R1) RECORD NAME/ INITIALS OF PERSON 11: ______

(650-651)

(R2) RECORD NAME/ INITIALS OF PERSON 12: ______

(652-653)

Q75 ASK ALL Code Route When was the last time you socialized with someone outside your family? [SA] (654)

你最近一次和家人以外的人一起进行社交活动是在什么时候？ [SA]

Within the last two days 1 Within the last week 2 Within the last month 3 Within the last six months 4 Longer ago than that 5

207

INSTRUCTION TO INTERVIEWER: Please read the following text to the respondent:

Now, let's move on to talk about the more formal aspects of socializing. What follows is a set of questions about: 1. Your national service experience [READ ONLY TO ALL MALE RESPONDENTS]. 2. Your participation in various kinds of voluntary organizations.

现在，让我们来谈谈比较正式的社交活动。接下来的问题是有关： 1。你服役的经验 [READ ONLY TO ALL MALE RESPONDENTS]. 2。你参与各类自愿团体的经验。

SECTION E: NATIONAL SERVICE ASK ALL MALE RESPONDENTS

Q76 ASK ALL MALE RESPONDENTS Code Route Did you perform any National Service duties? [SA] (655)

你有没有履行国民服役？[SA]

Yes 1 Q77 No 2 Q82

Q77 ASK ALL WHO PERFORMED NATIONAL SERVICE DUTIES - CHECK Q76 CODE 1 Code Route Do you presently have an assigned reservist unit?[SA] (656)

你目前是否属于哪个战备军人单位？ [SA]

Yes 1 Yes, but I have yet to go for my first ICT 2

No 3 I finished my reservist duties already 4

Q78 ASK ALL WHO PERFORMED NATIONAL SERVICE DUTIES - CHECK Q76 CODE 1 Code Route Do you still keep in touch with any of your army friends?[SA] (657)

你还有没有跟你军中的朋友保持联络？[SA]

Yes 1 Q79 No 2 Q80

208

Q79 ASK ALL WHO KEEP IN TOUCH WITH HIS ARMY FRIENDS - CHECK Q78 CODE 1 Can you please give me the name or initials of one of the army friends whom you still keep in touch with?

INSTRUCTION TO INTERVIEWER: Please record the name or initials of this army friend. Skip to Q81

请问你跟哪些军中的朋友保持联络，可不可以告诉我其中一人的名字或简称？

(R1) RECORD NAME/ INITIALS OF PERSON 13: ______

(658-659)

Q80 ASK ALL WHO PERFORMED NATIONAL SERVICE DUTIES - CHECK Q76 CODE 1 OR ALL WHO HAVE AN ASSIGNED RESERVIST UNIT OR FINISHED HIS RESERVIST - CHECK Q77 CODES 1 OR 4 When we go back for In-Camp Training (ICT), we often re-unite with our fellow unit personnel. We are more familiar with some of our camp-mates and less with others. For those whom we are more familiar with, we often stick together throughout the in-camp training period (e.g. go for breaks together etc).

FOR THOSE WHO HAVE AN ASSIGNED RESERVIST UNIT, ASK Can you please tell me who is your CLOSEST CAMP MATE ? Can you please provide me with a name or initial of this person?

FOR THOSE WHO HAVE FINISHED HIS RESERVIST DUTIES, ASK Can you please tell me who was your CLOSEST CAMP MATE ? Can you please provide me with a name or initial of this person?

INSTRUCTION TO INTERVIEWER: Please record the name or initials of this person.

当我们回营受训(ICT) 的时候，我们通常被安排跟同一组人在一起。在同一个营的同伴当中，我们会跟一些人比较熟。在受训期间，我们通常会跟那些较熟的人聚在一起(例如一起去小休等)

FOR THOSE WHO HAVE AN ASSIGNED RESERVIST UNIT, ASK 请问谁是你军营中最亲密的同伴呢？可不可以告诉我这个人的名字或简称？

FOR THOSE WHO HAVE FINISHED HIS RESERVIST DUTIES, ASK 请问谁是你以前在军营中最亲密的同伴呢？可不可以告诉我这个人的名字或简称？

(R1) RECORD NAME/ INITIALS OF PERSON 13: ______

(660-661)

Q81 ASK ALL WHO GAVE A NAME/ INITIAL IN Q79 or Q80 Code Route Thinking of your closest camp-mates, do you ever do things together outside of your ICT? For (662) example, meeting up for a meal, engage in games, train for the IPPT, chit-chat etc.[SA] 想想你最亲密的军营同伴，你们除了回营受训之外，有没有在一起做其它的事呢？例如，相约吃饭、一起玩游戏、一起锻炼身体以应付体能测验（IPPT ）、聊天等。 [SA]

Yes 1 No 2

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Q82 ASK ALL Code Route Do you currently PLAY ANY FORM OF SPORTS or EXERCISE ON A REGULAR BASIS , (663) meaning at least once a fortnight? [SA]

你目前有没有进行任何体育活动或者运动，就是说至少每两个星期一次？ [SA]

Yes 1 Q83 No 2 Q84

Q83 ASK ALL WHO PLAY SPORTS OR EXERCISE REGULARLY - CHECK Q82 CODE 1 Can you please tell me the name or initials of your MOST REGULAR SPORTS OR EXERCISE PARTNER ?

INSTRUCTION TO INTERVIEWER: Please record the name/ initials of this person.

请问最常跟你一起进行体育活动或运动的人是谁？可不可以告诉我他的名字或简称？

(R1) RECORD NAME/ INITIALS OF PERSON 14: ______

(664-665)

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SECTION F: VOLUNTARY ORGANIZATIONS

Q84 ASK ALL Code Route SHOWCARD (666) Over the past six months, have you ATTENDED A GET-TOGETHER OR MEETING in any of these types of organizations? [MA]

在过去6个月内，你有没有参加过以下任何机构的聚会或会议？ [MA]

Religio us groups (e.g. cell group in churches, Islamic religious classes, The Soka As sociation 01 etc.) Charity or welfare organizations (e.g. Singapore Cheshire Home, The Salvation Army, Homes 02 for the Aged etc.) Community centres and clubs 03 Country clubs (e.g. CDANS, Punggol Marina etc.) 04 Sports associations (e.g. SAFRA branches, Marine Castle Football Club, Kallang Sea Sports 05 Club etc.) Private educational institutions (e.g. night courses for private degrees, Yamaha Music 06 Academy, Tertiary institutions etc.) Ethnic, racial or national organizations (e.g. The People's Association, MENDAKI, CDAC etc.) 07 Special interest groups (e.g. issue-oriented and lobby groups like AWARE, Nature Society etc.) 08 Neighbourhood associations (e.g. Citizen Consultative Committee, Residents' Committee, 09 Grassroot Club etc.) Parent -Teacher associations 10 Professional organizations/ groups (e.g. AMP, The Singapore Law Society etc.) 11 Political Party (e.g. PAP, PAP youth) 12 Others (pls. specify) ______13 Cultural Exchange 14 Not sure/ Cant' say/Can't remember 29 None of the above 30

Q85 ASK ALL WHO GAVE A RESPONSE IN Q84 - SELECTED CODES 1 - 14 IN Q84 From among the people whom you see or meet in these organizations, who have you spoken to most recently? Please give me the names or initials of these people.

INSTRUCTION TO INTERVIEWER: Please record the names/ initials of people mentioned.

你在这些机构见到或遇到的人当中，你最近一次跟谁谈过话？请告诉我这些人的名字或简称？

(R1) RECORD NAME/ INITIALS OF PERSON 1 5: ______

(669-670)

(R2) RECORD NAME/ INITIALS OF PERSON 16 : ______(671-672)

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SECTION G: OTHER NAMES/ ETHNIC PROBE

INSTRUCTION TO INTERVIEWER: Please compile a list of all the names that were mentioned in all the questions thus far, in the separate sheet of paper.

Q86 ASK ALL Code Route SHOW COMPILED LIST OF NAMES (673) Please take a look at this list. Is there anyone who is important or close to you but whose name does not show up on this list?

INSTRUCTION TO INTERVIEWER: If the respondent selects Code 2 here, please evaluate which option in Q88 should be asked. [SA]

请看这里列出的人。有没有任何对你重要或跟你亲近的人的名字没有列在这里？ [SA]

Yes 1 Q87 No 2 Q88

Q87 ASK ALL WHO MENTIONED THAT THE NAME OF SOMEONE IMPOR TANT IS MISSING FROM THE LIST - CHECK Q86 CODE 1. ASK RESPONDENTS TO NAME THE MOST IMPORTANT TWO IF THERE ARE MORE THAN TWO. Can you please tell me the name or initials of this person whose name is currently missing from this list?

可不可以告诉我目前这里没有列出的这个人的名字或简称？

(R1) RECORD NAME/ INITIALS OF PERSON 1 7: ______

(674-675)

(R2) RECORD NAME/ INITIALS OF PERSON 18 : ______

(676-677)

INSTRUCT ION TO INTERVIEWER: Please record the ethnicity of all the names that were mentioned in all the questions thus far, in the separate sheet of paper and proceed to ask Q88 .

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Q88 ASK ALL I see that you HAVE NOT NAMED ANY ______[READ ETHNIC GROUP THAT IS OPPOSITE OF THE RESPONDENT'S AND THAT IS MISSING FROM THE LIST - START FROM TICK] persons. Do you know people who are [READ FROM TICK] whom you could include in this list. [READ FROM TICK] people whom you can talk to, laugh, joke or just have a good time? INSTRUCTION TO INTERVIEWER: Please rotate the ethnic group to be read, starting from tick: ( ) Chinese ( ) Malay ( ) Indian ( ) Non-Singaporean FOR ALL NON-CITIZEN , PLEASE READ OUT ‘SINGAPOREAN’ AS AN ETHNIC GROUP TO THE RESPONDENT OR I see that you HAVE NAMED A FEW ______[READ ETHNIC GROUP THAT IS OPPOSITE OF THE RESPONDENT'S - START FROM TICK] persons. Do you know people who are [READ FROM TICK} whom you could include in this list. [READ FROM TICK] people whom you can talk to, laugh, joke or just have a good time? INSTRUCTION TO INTERVIEWER: Please rotate the ethnic group to be read, starting from tick: ( ) Chinese ( ) Malay ( ) Indian ( ) Non-Singaporean PROBE Is there anyone else? Any others? 我看你这里并没有列出任何HAVE NOT NAMED ANY ______[READ ETHNIC GROUP THAT IS OPPOSITE OF THE RESPONDENT'S AND THAT IS MISSING FROM THE LIST - START FROM TICK] 人。请问你是否认识任何[READ FROM TICK] 人，可以把他的名字放在这里吗？就是，你可以跟他一起谈话、开玩笑或一起玩乐的[READ FROM TICK] 人？ INSTRUCTION TO INTERVIEWER: Please rotate the ethnic group to be read, starting from tick: ( ) Chinese ( ) Malay ( ) Indian ( ) Non-Singaporean

FOR ALL NON-CITIZEN , PLEASE READ OUT ‘SINGAPOREAN’ AS AN ETHNIC GROUP TO THE RESPONDENT OR 我看你这里列出了几位HAVE NAMED A FEW ______[READ ETHNIC GROUP THAT IS OPPOSITE OF THE RESPONDENT'S - START FROM TICK] 人。你还认不认识其他人？你还可以告诉我更多的名字或简称吗？请问你是否认识任何[READ FROM TICK] 人，可以把他的名字放在这里吗？就是，你可以跟他一起谈话、开玩笑或一起玩乐的[READ FROM TICK] 人？ INSTRUCTION TO INTERVIEWER: Please rotate the ethnic group to be read, starting from tick: ( ) Chinese ( ) Malay ( ) Indian ( ) Non-Singaporean Probe 还有其他人吗？还有其他的吗?

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(R1) RECORD NAME/ INITIALS OF PERSON 19: ______

(678-679)

(R2) RECORD NAME/ INITIALS OF PERSON 20: ______

(680-713)

Q89 RECORD ETHNIC GROUP READ OUT TO THE RESPONDENTS IN Q88 [SA] Code Route (714) Chinese 1 Malay 2 Indian 3 Non-Singaporean 4 Singaporean 5

Q90 RECORD NO. OF TIMES YOU HAD TO PROBE THE RESPONDENT FOR AN ANSWER IN Q88

(R1) RECORD NO. OF TIMES YOU HAD TO PROBE RESPONDENT: (715- 716)

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SECTION H: IDENTITY

INSTRUCTION TO INTERVIEWER: Please read the following text to the respondent:

In the last half an hour or so, I have asked you several questions about your job, family, social life etc. Now, I am going to ask you some questions pertaining to your SENSE OF IDENTITY .

刚才我们谈过了你的工作、家庭、社交生活等。现在，我要问你一些有关自我认同的问题。

Q91 ASK ALL DROPCARD I am going to read to you, a list of things that different people value. Some people say these things are very important to them while others say they are not as important. Using a scale of 1 to 5 where '1' represents 'Not at all important' and '5' represents 'Especially important', please tell me how important each of these statements is to you. [SA]

我要念出一些人们重视的东西。有些人觉得这些东西对他们很重要，有些人却觉得不重要。请你用1到5的评分表来告诉我以下各项对你有多重要。这里1表示完全不重要，而5表示特别重要。[SA]

Not at all Not too Quite Very Especially important - important - important - important - important - 1 2 3 4 5 (722) (R1) Being financially secure 1 2 3 4 5 (723) (R2) Being married 1 2 3 4 5 (724) (R3) Having children 1 2 3 4 5 (725) (R4) Having faith in God 1 2 3 4 5 (726) (R5) Having nice things 1 2 3 4 5 (727) (R6) Being cultured 1 2 3 4 5 (728) (R7) Having a fulfilling job 1 2 3 4 5 (729) (R8) Being self-sufficient and not having to depend on 1 2 3 4 5 others (730) (R9) Having friends 1 2 3 4 5 (731) (R10) Being myself 1 2 3 4 5 (732) (R11) Being able to speak the language of my ancestors 1 2 3 4 5

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Q92 ASK ALL DROPCARD Using a scale of 1 to 5 where '1' represents ‘Strongly disagree’ and '5' represents ‘Strongly agree’, can you please tell me to what extent do you agree or disagree with the following statements? [SA]

请用1到5的评分表，告诉我你有多同意或不同意以下的句子？这里1表示非常不同意，而5表示非常同意。 [SA]

Strongly Disagree - 2 Neither Agree - 4 Strongly disagree - 1 agree nor agree - 5 disagree - 3 (733) (R1) I would rather be a citizen of Singapore than a 1 2 3 4 5 citizen of any other country in the world (734) (R2) There are some things about Singapore today that 1 2 3 4 5 make me feel ashamed of Singapore (735) (R3) Generally speaking, Singapore is a better country 1 2 3 4 5 than most other countries

Q93 ASK ALL DROPCARD Now, using a scale of 1 to 5 where '1' represents 'Strongly disagree' and '5' represents 'Strongly agree', can you please tell me to what extent do you agree or disagree with the following statements? [SA]

现在，请用1到5的评分表，告诉我你有多同意或不同意以下的句子？这里1表示非常不同意，而5表示非常同意。 [SA]

Strongly Disagree - 2 Neither Agree - 4 Strongly disagree - 1 agree nor agree - 5 disagree - 3 (736)

(R1) To a great extent, my life is controlled by accidental 1 2 3 4 5 happenings - I take things as they come (737) (R2) I feel that what happens in my life is mostly 1 2 3 4 5 determined by powerful people (738) (R3) In life, I determine what I do 1 2 3 4 5 (739) (R4) When I need help, I can organize and request for 1 2 3 4 5 people to help me (740) (R5) In life, I am quite willing to trust people 1 2 3 4 5

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Q94 ASK ALL Code Route If you have the opportunity, would you migrate overseas? [SA] (741)

如果你有机会，你会不会移民海外？ [SA]

Yes 1 No 2 Maybe 3 Don't know/ Not sure/ Can't say 4

Q95 ASK ALL Code Route SHOWCARD (742) How would you describe the Singapore society today? Please read through the following statements and let me know which one/s you agree with.[MA]

你会怎样形容现在的新加坡社会？请仔细读以下的句子，然后告诉我你同意哪个/哪些。[MA]

Singapore is undergoing enormous transformations 1 The pace of change is fast 2 The next few years will be stressful 3 The next few years will be stressful but exciting 4 I feel the pressure to upgrade my skills to stay relevant 5 We are in for tough times 6 I am looking forward to better days 7 None of the above 8

Q96 ASK ALL Code Route In comparison to five years ago, would you say that life today is better, worse or the same for (743) you? [SA]

跟5年前相比，你会说你现在的生活比较好、较差，还是一样？[SA]

Better 1 Same 2 Worse 3 Don't know/ Not sure/ Can't say 4

INSTRUCTION TO INTERVIEWERS: Please proceed to record the personal particulars of the respondent's network members in the separate sheet of paper.

CLOSE INTERVIEW - THANK RESPONDENT

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INTERVIEWERS: PLEASE REMEMBER TO COMPLETE QUESTIONS ON SECTION I ( INTERVIEW CONDITIONS) BELOW.

SECTION I: INTERVIEW CONDITIONS

TO BE ANSWERED BY THE INTERVIEWER.

Q97 ALL INTERVIEWERS Code Route Where was the interview carried out? [SA] (744)

Immediately outside the person's home (at the doorway) 1 In the person's home 2 At another place other than the person's home 3

Q98 ALL INTERVIEWERS Code Route Was anyone else present during the interview? 'Present' means in the same room.[SA] (745)

Yes, for most of the interview 1 Yes, for some of the interview 2 Yes, but only for a minute or two 3 No, not at any time 4

Q99 INTERVIEWERS ANSWER THIS QUESTION IF CODE 1 & 2 SELECTED IN Q98 Code Route Who else was present?[MA] (746)

Spouse 1 Other adult household member (18 or over - roughly by observation) 2 Teenager (13 - 18) 3 Child or infant (under 13) 4 Friends, visitor 5 Others (Please specify:______) 6

Q100 ALL INTERVIEWERS Code Route Did the respondent have difficulty understanding the questions?[SA] (747)

Yes, great difficulty 1 Yes, some difficulty 2 No, none at all 3

Q101 ALL INTERVIEWERS Code Route What was the respondent's attitude during the interview?[SA] (748)

Friendly, eager, volunteered information 1 Cooperative, but not particularly enthusiastic 2 Indifferent or bored 3 Often irritated or hostile - seemed anxious to get it over with 4 Hard to tell 5

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Q102 ALL INTERVIEWERS Code Route How would you describe the respondent's mood during the interview? [SA] (749)

Elated 1 Happy 2 Neutral 3 Sad 4 Depressed 5

Declaration by Su rvey Officer

I hereby certify that this interview carried out and recorded by me today, is true and accurate, and in accordance with the survey methodology, specified instructions, and the ESOMAR Code of Practice.

______Signature of Survey Officer

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