Structure and information in spatial segregation

Ethnoracial residential segregation is a complex, multiscalar phenomenon with immense moral and economic costs. Modeling the structure and dynamics of segregation is a pressing problem for sociology and urban planning, but existing methods have limitations. In this paper, we develop a suite of metho...

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Bibliographic Details
Published in:Proceedings of the National Academy of Sciences - PNAS 2017-10, Vol.114 (44), p.11591-11596
Main Author: Chodrow, Philip S.
Format: Article
Language:English
Subjects:
Artificial intelligence
Cities
Computer Simulation
Continental Population Groups
Decomposition
Economic impact
Economic models
Ethnic Groups
Humans
Information theory
Models, Theoretical
Multiculturalism & pluralism
Open source software
Physical Sciences
Residence Characteristics
Segregation
Social Sciences
Social Segregation
Socioeconomic Factors
Sociology
Spatial analysis
United States
Urban planning
Urban Population
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Summary:Ethnoracial residential segregation is a complex, multiscalar phenomenon with immense moral and economic costs. Modeling the structure and dynamics of segregation is a pressing problem for sociology and urban planning, but existing methods have limitations. In this paper, we develop a suite of methods, grounded in information theory, for studying the spatial structure of segregation. We first advance existing profile and decomposition methods by posing two related regionalization methods, which allow for profile curves with nonconstant spatial scale and decomposition analysis with nonarbitrary areal units. We then formulate a measure of local spatial scale, which may be used for both detailed, within-city analysis and intercity comparisons. These methods highlight detailed insights in the structure and dynamics of urban segregation that would be otherwise easy to miss or difficult to quantify. They are computationally efficient, applicable to a broad range of study questions, and freely available in open source software.
ISSN:0027-8424
1091-6490
DOI:10.1073/pnas.1708201114