Return to search

Deconstructing 'Segregation' : Exploring South Asian Geographies and Inequality in Britain

This thesis investigates the relationship between the spatial concentration of South Asian ethnic groups and experiences of inequality in education, employment and health. Ethnic and racial segregation has become of increasing concern in Britain over the past decade, but there has been little research that has examined the relationship between the spatial concentration of minority ethnic groups and their socio-economic outcomes in various domains. This study sets out to address this gap in the literature. In recent years, segregation has become an increasingly ambiguous and value-laden concept. The shift in its meaning to denote the self-segregation of minority ethnic groups in Britain has made it an increasingly problematic concept for investigating inequality. At the same time the rise to prominence of research on segregation in the US has greatly influenced academic research on the matter in Britain. In this thesis I adopt a more critical approach to segregation in Britain by framing South Asian geographies within a socialhistorical context by taking account of the nature of migration and settlement of South Asians to Britain, and the structural context, namely discriminatory housing and labour market pOlicies, within which this occurred. In light of this, I suggest that a more appropriate measure of spatial segregation is neighbourhood deprivation, which more accurately reflects the material disadvantage of many areas of high minority ethnic concentration. Thus, the focus of my empirical analysis looks at the extent to which the divergence in socio-economic outcomes across geographies for South Asian and White British ethnic groups is related to the South Asian concentration of neighbourhoods, and the extent to which this is associated with levels of neighbourhood deprivation. I also look at the extent to which differences between the South Asian and White British ethnic groups are associated with neighbourhood co-ethnic concentration and deprivation. I address the research question using two national datasets. Comprehensive neighbourhood data available from 2001 Census tabular data is used to obtain data measuring the ethnic composition of neighbourhoods and the employment, education and health outcomes of ethnic groups at the neighbourhood level. With this data I examine the relationship between levels of neighbourhood South Asian concentration, levels of neighbourhood deprivation, and outcomes in education, employment and health for Indian, Pakistani, Bangladeshi, and White British ethnic groups. The second dataset I make use of is the 2005 Citizenship Survey which includes additional requested data on the ethnic composition and deprivation levels of neighbourhoods for respondents in the survey. I use multilevel logistic regression methods to determine the extent to which the neighbourhood context matters. I find neighbourhood deprivation to be more important in explaining the divergence in education, employment, and health across geographies than levels of South Asian concentration for all ethnic groups. I find the negative association between Pakistani and Bangladeshi concentration and education and employment outcomes to be explained when levels of neighbourhood deprivation are considered. In terms of inequality, while, on average, the Indian group report better or equal socio-economic outcomes compared with the White British group, the disadvantage experienced by Pakistanis and Bangladeshis is not explained by levels of co-ethnic concentration. Factors such as human capital and household income are shown to be more important. My evidence suggests that policy approaches to tackling inequality should focus on area deprivation, rather than the ethnic composition of neighbourhoods.

Identiferoai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:520706
Date January 2010
CreatorsKapoor, Nisha
PublisherUniversity of Manchester
Source SetsEthos UK
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation

Page generated in 0.0016 seconds