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The Measurement of Ethnic Segregation in the Netherlands: Differences Between Administrative and Individualized Neighbourhoods

Overview of attention for article published in European Journal of Population, March 2018
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Title
The Measurement of Ethnic Segregation in the Netherlands: Differences Between Administrative and Individualized Neighbourhoods
Published in
European Journal of Population, March 2018
DOI 10.1007/s10680-018-9479-z
Pubmed ID
Authors

Bart Sleutjes, Helga A. G. de Valk, Jeroen Ooijevaar

Abstract

The debate on residential segregation often focuses on the concentration of migrant groups in specific neighbourhoods and its presumed effects on, e.g. personal life chances and social inclusion. However, cross-regional and international comparisons of segregation are hampered by differences in the size and delineation of the spatial units that are used for its measurement: the Modifiable Areal Unit Problem. This paper therefore measures segregation for scalable 'individualized neighbourhoods', defined by a predefined number of closest neighbours instead of by administrative or statistical boundaries. This approach allows for measuring segregation levels and patterns across different spatial scales, ranging from the micro-scale (50 neighbours) to larger spatial areas (51,200 neighbours). Using population register data from the Netherlands, we study the segregation of four different migrant origin groups across individualized neighbourhoods at eleven spatial scales. Outcomes are compared to those found using administrative neighbourhoods. We are especially interested in how levels and patterns of segregation change with an increase in scale level. Our findings indicate that segregation levels and patterns are different across various spatial scales, and the most relevant spatial scale is also group-specific. Measuring segregation while using scalable individualized neighbourhoods seems an appropriate way to deal with both the multiscalar nature of segregation and the large within-district variety associated with it.

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The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 20%
Lecturer 3 10%
Student > Master 3 10%
Researcher 3 10%
Student > Bachelor 2 7%
Other 5 17%
Unknown 8 27%
Readers by discipline Count As %
Social Sciences 10 33%
Environmental Science 3 10%
Computer Science 2 7%
Economics, Econometrics and Finance 2 7%
Energy 2 7%
Other 3 10%
Unknown 8 27%