Maps and Intelligence to Support the Targeting of Aimhigher Programme Activities in the North East

CURDS Newcastle University Mike Coombes Emmanouil Tranos Simon Raybould Maps and intelligence to support the targeting of Aimhigher programme activities in the North East Report to the Aimhigher team in the North East November 2007 Summary This is the Final Report by Newcastle University‟s Centre for Urban and Regional Development Studies (CURDS) to the Aimhigher programme in the North East region (Ah_NE). It is one of two key outputs from a research study: central to the work has been the production of maps to help Ah_NE target Aimhigher activities on the priority groups identified by the recent Guidance (2007) (HEFCE/DfES/LSC 2007). Alongside the maps – supplied on CD – this report provides supporting intelligence. In particular, the report documents the distribution of priority groups across the sub-regions through which the Ah_NE programme is delivered. It also compares different ways of identifying priority groups. The report ends by outlining some approaches to targeting which maps and/or the supporting intelligence could be used for. Acknowledgements The research team are grateful for the Guidance (2007) of Richard Dodgson (Ah_NE) and for the comments of potential users on early versions of the maps. Census output is Crown copyright and is reproduced with permission of the Controller of HMSO and the Queen's Printer for Scotland. Glossary of abbreviations used in the report Ah_NE Aimhigher programme in the North East Guidance (2007) Good Practice Guidance 2007/12 by HEFCE/DfES/LSC IMD Index of Multiple Deprivation 2004 LA local authority area LSOA Lower-level Super Output Area NS-SEC National Statistics Socio-Economic Classification OA Output Area PLASC pupil level annual schools census 2 Introduction 1. As one of the outcomes of the Comprehensive Spending Review (2007), government minister Bill Rammell announced that there would be continuing funding until at least 2011 for the Aimhigher programme to widen participation in higher education. This news should be seen in the context of the research upon current practice in widening participation, reported by HEFCE (2006), which concluded that “[b]etter targeting is required” (p. 43). 2. The recently published policy Guidance (2007) document “Higher education outreach: targeting disadvantaged learners” (HEFCE/DfES/LSC 2007) – which will from hereon be referred to as “Guidance (2007)” – sets out a three stage process for Aimhigher partnerships to follow. In the Guidance (2007) there are key principles, but there is also flexibility over how these principles should be implemented. This report aims to support the Aimhigher programme in the North East (Ah_NE) by providing intelligence needed to implement the first stage of targeting. To be specific, the Guidance (2007 page 11 para 39) calls for all Aimhigher partnerships to identify “the schools, colleges and communities where disadvantage is concentrated and where effort and resources should be concentrated.” 3. The research which produced this report also generated a large set of maps which are detailed in the Annex and supplied on a CD in parallel to this report. The principal aim for the report itself is to provide the supporting intelligence so that the maps can be used as effectively and appropriately as possible. There are four requirements: explaining the nature of the prioritisation depicted on the maps provide on the CD accompanying this report, summarising the patterns shown in the mapped distribution of priority groups across the region, commenting on the difference between alternative ways of identifying priority groups, and then discussing a number of options for targeting both within and beyond the first stage of the approach outlined in the Guidance (2007). These tasks are taken up in turn in the main sections of the report that follow. 3 Mapping Priority Groups 4. The maps are presented in a format that is familiar in the field of public policy: every area is shaded according to its level of priority, with a selection of other features also shown to help the user to find the areas of most interest to them. As well as selecting the features to help users orientate, it is essential to make three critical decisions in the data analysis lying behind the shading of areas by level of priority. First a decision needs to be taken on which statistical measure to use to assess each area‟s level of priority. Second the set of geographical areas to be analysed must be chosen: for example they could be local authority areas (LAs) although, in fact, much smaller areas will be needed here. Third a decision is needed on the way the measured values are divided up (eg. it may or may not be necessary to split up the areas which are not high priority, so as to identify those which are the lowest priority of all). Although there are „pointers‟ in the guidelines to help with all these decisions, it is important to recognise that decisions did have to be made. The remainder of this part of the report describes the decisions made and the alternatives which were considered by Ah_NE before the final set of maps was produced. Which statistical measure would best identify areas of priority? 5. In the Guidance (2007) it is clear that targeting at this initial stage should identify the areas where the potential Aimhigher programme participants are most likely to need encouragement and/or support before they will actively consider participating in further or – perhaps especially – higher education. It is worth understanding the underlying process here: targeting can be done by area because the social and economic „drivers‟ of housing markets tend to create neighbourhoods which mostly include people with similar characteristics, especially in terms of their level of affluence or poverty, and the results is that some areas house concentrations of young people who do less well in terms of education (Raffo et al 2007). 6. Robertson and Hillman (1997) reviewed mounting evidence of strong variation between neighbourhoods in their residents‟ participation rates in education, with this variation found to be related to areas‟ level of poverty. Within the 4 North East itself, Conway et al (2002) and Coombes and Raybould (2003) showed the strength of the association between neighbourhood deprivation and higher education participation across the adult age range. Although the Guidance (2007) locates the root of low participation at the household scale – that is, participation is least likely by young people from households where neither parent had experienced higher education – it then recognises that their lower levels of qualification mean that such parents are unlikely to have high-status or highly paying jobs. Thus the neighbourhoods to prioritise for Aimhigher will be those where there are few parents with degrees or similar qualifications, few parents with high-status jobs, and there is also a high incidence of poverty or deprivation. 7. In relation to the first of these factors, Cassen and Kingdon (2007) have found an association between children‟s educational attainment at school and the proportion of parents in the neighbourhood with low qualifications. In fact the Guidance (2007) focusses on the other two factors, probably because they are more readily measured with available data. Of these two, the Guidance (2007) places greater emphasis on the deprivation indicator; it may be that one reason for emphasising deprivation is that targeting analyses can then use the officially approved Index of Multiple Deprivation (IMD). Although the IMD offers a range of different sub-indexes (including one which specifically relates to education in fact), the Guidance (2007) is clear that the overall IMD scores is to be used for targeting analyses. Which areas should be used for analyses in support of targeting? 8. Given the assumption in the Guidance (2007) that low participation is primarily rooted at the household scale, it follows that targeting by area is at least in part acting as a „proxy‟ for the targeting by household. As is usual with targeting, the main reason for this strategy is that there is a lack of readily available data at the household scale. One consequence is that it is usually assumed that targeting is best carried out using the smallest possible areas; in this way, the analysis is as close as possible to the ideal scale of the individual household, and also it minimises the mixing of more and less deprived households which will tend to be found with larger areas. In practice, this means using what are termed Lower-level Super Output Areas (LSOAs) because they are the smallest areas for which IMD data can be obtained. 5 9. As will be discussed in more detail in a later section of this report, it is possible to get some data relevant to targeting Aimhigher activities for smaller areas. These smaller areas are Census 2001 Output Areas (OAs): each OA houses about 200 households on average, whereas the average LSOA is roughly seven times larger. Even so, OAs will not necessarily be more appropriate for targeting by area. Many studies have shown educational participation and outcomes to be shaped by neighbourhood „ethos‟ as well as by characteristics of students and their households (Coombes & Raybould 1997). What remains uncertain is the exact scale over which the neighbourhood influences operate (cf. Bolster et al 2007). It remains possible that, although they are larger, LSOAs are a closer match to the scale at which socio-cultural factors operate to produce the neighbourhood effects observed in much educational research (eg. Universities of the West of England and Nottingham 2007). Which sets of IMD values should be identified on the maps? 10. In the Guidance (2007) it is suggested that Aimhigher efforts be targeted on residents of those LSOAs which are among the country‟s most deprived 13,000 LSOAs; these areas include roughly 40% of the population.

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