This thesis investigates 'self-segregation,' the voluntary separation and clustering of ethnic groups within a diverse environment that ostensibly provides opportunities for intergroup contact. While previous research has demonstrated self-segregation within such settings, using either self-reports, observations of behaviour, or social network analysis (SNA), such studies tend to be mono-methodological and cross-sectional. I review this literature in Chapter 1. I then present three empirical chapters which provide both longitudinal data and comparisons between observations, surveys, and SNA: Chapter 2, with two observational studies of seating patterns in a diverse sixth form cafeteria (Studies 1 and 2), and a third observational study in a diverse secondary school (Study 3); Chapter 3, where I report an SNA study collected from the first-year students at the same secondary school (Study 4); and Chapter 4, where I report the results from a self-report survey in the sixth form college, where students indicate their cafeteria seating preferences (Study 5). In Chapter 5, I discuss these findings, summarising 1) the strong self-segregation, and inclination towards self-segregation, found in all studies; 2) the comparisons between the two educational settings, where younger students were both more likely to be gender segregated, and to increase in ethnic integration over time; 3) the greater inclination of Asian British students than White British students to ethnically integrate; and 4) the need for further research triangulating multiple methods. From these conclusions, I suggest implications for targeted interventions, and argue the continued (and indeed, heightened) need for the contributions of social psychologists in public and policy discourse on ethnic integration.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:730373 |
Date | January 2016 |
Creators | Floe, Christina E. |
Contributors | Wölfer, Ralf ; Hewstone, Miles |
Publisher | University of Oxford |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | https://ora.ox.ac.uk/objects/uuid:030ab091-b6e6-4042-85b7-6b5e85f6c3b3 |
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