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<title>Spatial Modelling Research Group </title>
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<rdf:li rdf:resource="http://hdl.handle.net/1983/956"/>
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<dc:date>2013-05-13T09:02:07Z</dc:date>
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<title>Geographical statistics and the grid: grid-enabled modelling of local and global geographies</title>
<link>http://hdl.handle.net/1983/1059</link>
<description>Geographical statistics and the grid: grid-enabled modelling of local and global geographies
Harris, RJ; Brunsdon, Chris; Grose, Chris
Standard indexes of poverty and deprivation are rarely sensitive to how the causes and consequences of deprivation have different impacts depending upon where a person lives. More geographically minded approaches are alert to spatial variations but are also difficult to compute using desktop PCs. This conference paper reports on a project to develop a method of spatial analysis known as ‘geographically weighted regression’ (GWR) to run in the high power computing environment offered by ‘Grid computation’ and e-social science. GWR, like many other methods of spatial analysis, is characterised by multiple repeat testing as the data are divided into geographical regions and also randomly redistributed many times to simulate the likelihood that the results obtained from the analysis are actually due to chance. Each of these tests requires computer time so, given a large dataset such as the UK Census statistics, running the analysis on a standard machine can take a long time! Fortunately, the computational grid is not standard but offers possibility to speed-up the process by running GWR’s sequences of calibration, analysis and non parametric simulation in parallel.
Conference presentation
</description>
<dc:date>2008-02-20T00:00:00Z</dc:date>
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<item rdf:about="http://hdl.handle.net/1983/956">
<title>Primary schools, markets and choice: studying polarization and the core catchment areas of schools</title>
<link>http://hdl.handle.net/1983/956</link>
<description>Primary schools, markets and choice: studying polarization and the core catchment areas of schools
Harris, RJ; Johnston, RJ
In this paper we distinguish polarization from other conceptions of segregation by conceiving the former as a local phenomenon. To this end we argue that evidence for any school-level separation of ethnic groups must be sought and contextualised within the local markets within which schools operate. By determining the ‘core catchment’ areas of primary schools from geographical micro-data reporting where pupils reside and which school they attend within the study region of Birmingham, England, so we estimate where and by how much schools compete with each other across spaces of admission, consider whether the ethnic compositions of those spaces are representative of the actual intakes of schools, and identify evidence of post-residential sorting and ethnic polarization, where locally competing schools draw markedly different student intakes.
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<dc:date>2007-10-17T08:45:55Z</dc:date>
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<item rdf:about="http://hdl.handle.net/1983/955">
<title>School choice, social competition and ethnic segregation</title>
<link>http://hdl.handle.net/1983/955</link>
<description>School choice, social competition and ethnic segregation
Harris, RJ; Johnston, RJ
Powerpoint presentation (PDF file format) of a conference session
</description>
<dc:date>2007-10-12T00:00:00Z</dc:date>
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<item rdf:about="http://hdl.handle.net/1983/938">
<title>Neighborhoods, ethnicity and school choice: developing a statistical framework for geodemographic analysis</title>
<link>http://hdl.handle.net/1983/938</link>
<description>Neighborhoods, ethnicity and school choice: developing a statistical framework for geodemographic analysis
Harris, RJ; Johnston, RJ; Burgess, SM
Geodemographics 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.&#13;
&#13;
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.
Preprint accepted for publication in Population Research and Policy Review
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<dc:date>2007-05-23T10:44:29Z</dc:date>
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