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Classifying Pupils by Where They Live: How Well Does This Predict Variations in Their GCSE Results?

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  • Richard Webber

    (Centre for Advanced Spatial Analysis, Department of Geography, University College London, Pearson Building, Gower Street, London, WCIE 6BT, UK, richardwebber@blueyonder.co.uk)

  • Tim Butler

    (Department of Geography, King's College London, Strand, London, WC2R 2LS, UK, tim. butler@kcl.ac.uk)

Abstract

This paper summarises key findings resulting from the appending of the neighbourhood classification system Mosaic to the records of the Pupil Level Annual School Census (PLASC) within the National Pupil Database (NPD) of the Department for Education and Skills (DfES). The most significant of these findings is that, other than the performance of the pupil at an earlier Key Stage test, the type of neighbourhood in which a pupil lives is a more reliable predictor of a pupil's GCSE performance than any other information held about that pupil on the PLASC database. Analysis then shows the extent to which the performance of pupils from any particular type of neighbourhood is also incrementally affected by the neighbourhoods from which the other pupils in the school they attend are drawn. It finds that whilst a pupil's exam performance is affected primarily by the social background of people he or she may encounter at home, the social background of fellow school pupils is of only marginally lower significance. These findings suggest that so long as pupils' GCSE performances are so strongly affected by the type of neighbourhood in which they live, a school's league position bears only indirect relationship to the quality of school management and teaching. A better measurement of the latter would be a league table system which took into account the geodemographic profile of each school's pupil intake. The paper concludes with discussion of the relevance of these findings to the sociology of education, to the debate on consumer choice in public services, to the general appropriateness of adjusting public-sector performance metrics to take into account the social mix of service users and to parental strategies in the educational sector in particular.

Suggested Citation

  • Richard Webber & Tim Butler, 2007. "Classifying Pupils by Where They Live: How Well Does This Predict Variations in Their GCSE Results?," Urban Studies, Urban Studies Journal Limited, vol. 44(7), pages 1229-1253, June.
    • Handle: RePEc:sae:urbstu:v:44:y:2007:i:7:p:1229-1253
    DOI: 10.1080/00420980701302353
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    References listed on IDEAS

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    1. Ron Johnston & Deborah Wilson & Simon Burgess, 2005. "England's Multiethnic Educational System? A Classification of Secondary Schools," Environment and Planning A, , vol. 37(1), pages 45-62, January.
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    Cited by:

    1. Rebecca Allen & Anna Vignoles, 2016. "Can school competition improve standards? The case of faith schools in England," Empirical Economics, Springer, vol. 50(3), pages 959-973, May.
    2. Borooah, Vani & Dineen, Donal & Lynch, Nicola, 2009. "Which are the "best" schools in Ireland? Analysing feeder school performance using student destination data," MPRA Paper 75680, University Library of Munich, Germany.

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