3.8 Article

Population Grids for Analysing Long-Term Change in Ethnic Diversity and Segregation

Journal

SPATIAL DEMOGRAPHY
Volume 8, Issue 3, Pages 215-249

Publisher

SPRINGER INTERNATIONAL PUBLISHING AG
DOI: 10.1007/s40980-020-00071-6

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Funding

  1. Economic and Social Research Council [ES/L014769/1]
  2. ESRC [ES/L014769/1] Funding Source: UKRI

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Changes in the spatial patterns of ethnic diversity and residential segregation are often highly localized, but inconsistencies in geographical data units across different time points limit their exploration. In this paper, we argue that, while they are often over-looked, population grids provide an effective means for the study of long-term fine-scale changes. Gridded data represent population structures: there are gaps where there are no people, and they are not (unlike standard zones) based on population distributions at any one time point. This paper uses an innovative resource, PopChange, which provides spatially fine-grained (1 km by 1 km) gridded data on country of birth (1971-2011) and ethnic group (1991-2011). These data enable insight into micro-level change across a long time period. Exploring forty years of change over five time points, measures of residential ethnic diversity and segregation are employed here to create a comprehensive 'atlas' of ethnic neighbourhood change across the whole of Britain. Four key messages are offered: (1) as Britain's ethnic diversity has grown, the spatial complexity of this diversity has also increased, with greater diversity in previously less diverse spaces; (2) ethnic residential segregation has steadily declined at this micro-scale; (3) as neighbourhoods have become more diverse, they have become more spatially integrated; (4) across the whole study period, the most dynamic period of change was between 2001 and 2011. While concentrating on Britain as a case study, the paper explores the potential offered by gridded data, and the methods proposed to analyse them, for future allied studies within and outside this study area.

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