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Multiscale Segregation: Multilevel Modelling of Dissimilarity – Challenging the Stylized Fact that Segregation is Greater the Finer the Spatial Scale

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@article{34026c6169a549d89e91061151fc852b,
title = "Multiscale Segregation: Multilevel Modelling of Dissimilarity – Challenging the Stylized Fact that Segregation is Greater the Finer the Spatial Scale",
abstract = "A very large literature has explored the intensity of urban residential segregation using the index of dissimilarity. Several recent studies have undertaken such analyses at multiple spatial scales, invariably reaching the conclusion that the finer-grained the spatial scale the greater the segregation. Such findings over-state the intensity of segregation at finer spatial scales because they fail to take into account an argument made by Duncan et al. (1961) some seventy years ago that indices derived from fine-scale analyses must necessarily incorporate those from coarser scales, with the consequence that finer-scale segregation is invariably over-estimated. Moreover, most studies ignore stochastic variation that results in upward bias in the estimates of segregation. This paper demonstrates the importance of of a recently developed multilevel modelling procedure that identifies the ‘true’ intensity of segregation at every level in a spatial hierarchy net of its intensity at other levels, and net of stochastic variation This is illustrated by both a simulated data set and an empirical study of an English city, with the latter raising important substantive issues regarding the interpretation of segregation patterns and the processes underlying them.",
keywords = "segregation, dissimilarity, scale, multilevel modelling",
author = "David Manley and Kelvyn Jones and Ron Johnston",
year = "2019",
month = "7",
day = "3",
doi = "10.1080/00330124.2019.1578977",
language = "English",
volume = "71",
pages = "566--578",
journal = "Professional Geographer",
issn = "0033-0124",
publisher = "Taylor & Francis Group",
number = "3",

}

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TY - JOUR

T1 - Multiscale Segregation

T2 - Multilevel Modelling of Dissimilarity – Challenging the Stylized Fact that Segregation is Greater the Finer the Spatial Scale

AU - Manley, David

AU - Jones, Kelvyn

AU - Johnston, Ron

PY - 2019/7/3

Y1 - 2019/7/3

N2 - A very large literature has explored the intensity of urban residential segregation using the index of dissimilarity. Several recent studies have undertaken such analyses at multiple spatial scales, invariably reaching the conclusion that the finer-grained the spatial scale the greater the segregation. Such findings over-state the intensity of segregation at finer spatial scales because they fail to take into account an argument made by Duncan et al. (1961) some seventy years ago that indices derived from fine-scale analyses must necessarily incorporate those from coarser scales, with the consequence that finer-scale segregation is invariably over-estimated. Moreover, most studies ignore stochastic variation that results in upward bias in the estimates of segregation. This paper demonstrates the importance of of a recently developed multilevel modelling procedure that identifies the ‘true’ intensity of segregation at every level in a spatial hierarchy net of its intensity at other levels, and net of stochastic variation This is illustrated by both a simulated data set and an empirical study of an English city, with the latter raising important substantive issues regarding the interpretation of segregation patterns and the processes underlying them.

AB - A very large literature has explored the intensity of urban residential segregation using the index of dissimilarity. Several recent studies have undertaken such analyses at multiple spatial scales, invariably reaching the conclusion that the finer-grained the spatial scale the greater the segregation. Such findings over-state the intensity of segregation at finer spatial scales because they fail to take into account an argument made by Duncan et al. (1961) some seventy years ago that indices derived from fine-scale analyses must necessarily incorporate those from coarser scales, with the consequence that finer-scale segregation is invariably over-estimated. Moreover, most studies ignore stochastic variation that results in upward bias in the estimates of segregation. This paper demonstrates the importance of of a recently developed multilevel modelling procedure that identifies the ‘true’ intensity of segregation at every level in a spatial hierarchy net of its intensity at other levels, and net of stochastic variation This is illustrated by both a simulated data set and an empirical study of an English city, with the latter raising important substantive issues regarding the interpretation of segregation patterns and the processes underlying them.

KW - segregation

KW - dissimilarity

KW - scale

KW - multilevel modelling

UR - http://www.scopus.com/inward/record.url?scp=85060944212&partnerID=8YFLogxK

U2 - 10.1080/00330124.2019.1578977

DO - 10.1080/00330124.2019.1578977

M3 - Article

VL - 71

SP - 566

EP - 578

JO - Professional Geographer

JF - Professional Geographer

SN - 0033-0124

IS - 3

ER -