Neighborhoods, Ethnicity and School Choice: Developing a Statistical Framework for Geodemographic Analysis

Abstract

Neighborhoods, ethnicity and school choice: developing a statistical framework for geodemographic analysisGeodemographics as the 'analysis of people by where they live' has origins in urban sociology and social mapping, and is experiencing a renaissance in applied spatial demography. However, some commentators have expressed reservations about the statistical limitations of common geodemographic practices, especially focusing on the potential internal heterogeneity of the geodemographic groupings, as well as the problem of clearly identifying predictor variables that might account for or explain the socio-economic patterns revealed by geodemographic analyses.In this paper we argue that geodemographic typologies are structured methods for making sense of the spatial and socio-economic patterns encoded within complex datasets such as national census data. By treating geodemographics as more a framework than a tool for analysis in its own right we are able to integrate it with the flexibility and statistical conventions offered by multilevel modeling. We demonstrate this with a case study of whether pupils from different types of neighborhood in Birmingham, England are more or less likely to attend their nearest state funded secondary school and how that likelihood varies with the ethnic composition of the neighborhood. In so-doing we build on previous research suggesting that ethnic segregation between schools is at least equal to that between neighborhoods in England and speculate in this regard on the consequences of current Government plans to extend choice to parents within a schools market.2

Travel-to-school distances in Sweden 2000–2006: changing school geography with equality implications

“…In$this$paper$we$propose$that$the$effect$of$school$choice$on$the$educaZonal$opportuniZes$of$Swedish$ children$can$be$analyzed$by$focusing$on$travelBtoBschool$distances.$By$modeling$how$travelBtoBschool$ distances$are$influenced$by$individual$factors,$family$background,$and$by$the$neighborhood$context,$ it$will$be$possible$to$give$a$more$detailed$picture$of$how$school$choice$reshapes$the$social$and$ethnic$ composiZon$of$Swedish$schools.$This$study$of$travelBtoBschool$distances$thus$feeds$into$a$large$ internaZonal$research$field$and$debate$about$school$choice$ (Allen,$2007;$Burgess$et$al.,$2005;$Byrne,$ 2009;$Garcia,$2008;$Harris,$Johnston$and$Burgess$2007;$Noreisch,$2007;$Saporito$and$Lareau$1999;$ Seppanen$2003;$Karsten$et$al.,$2003)$and$changes$in$school$systems$ (Alegre$and$Ferrer$2010;$Taylor$ 2001;$Reay$2004).…”

Social Marketing and Public Health

“…One avenue of research is to design multi-level models, where the effects of residing in a particular neighbourhood type can be estimated relative to other causal factors (Harris et al, 2007). Another approach would be to use geodemographics as a data mining tool following the pragmatic definition of Hand et al (2001).…”

Putting the geography into geodemographics: Using multilevel modelling to improve neighbourhood targeting – a case study of Asian pupils in London

“…Nevertheless, what is less rarely considered is whether the differences between neighbourhood types can be judged statistically significant, at which scale of geodemographic classification the analysis is best undertaken or whether the differences between the neighbourhood types exist over and above that which can be explained by the use of other predictor variables. Rare exceptions to this are the paper by Harris et al (2007) who use multilevel modelling to provide a statistical framework for geodemographic analysis and, in that case, to look for evidence of neighbourhood effects; and the paper by Nnoaham et al (2010) who use multilevel modelling to ask whether geodemographic typologies explain variations in uptake in colorectal cancer screening. This paper extends that previous work with a case study targeting Asian pupils in residential parts of London.…”