Titlebook: New Methods for Measuring and Analyzing Segregation; Mark‘Fossett Book‘‘‘‘‘‘‘‘ 2017 The Editor(s) (if applicable) and the Author(s) 2017 D

矛盾心理

空气

Distinctions Between Displacement and Separation,liably established by examining the more widely used dissimilarity index (D). Specifically, S reliably indicates whether groups are separated and live apart from each other in different areas of the city and experience substantially different residential outcomes – at minimum with respect to area ra

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Kidnap

Unifying Micro-level and Macro-level Analyses of Segregation,o seamlessly connect macro-level segregation – as measured by the index score for a city – to micro-level processes of residential attainment. At the simplest level the value of any index placed in the difference of means framework can be obtained by performing an individual-level attainment analysi

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interior

Aspatial and Spatial Applications of Indices of Uneven Distribution,her conventional . formulations or in . formulations. Aspatial versions of segregation indices are familiar because they are widely used in empirical studies. They are obtained by applying any of the computing formulas reviewed here using data for non-overlapping, bounded areas such as census tracts

本能

Relevance of Individual-Level Residential Outcomes for Describing Segregation,widely in empirical analyses for more than five decades and each has been reviewed many times in methodological studies. Until now little attention has been given to the substantive relevance of the individual-level residential outcomes each index registers. In this chapter I argue that it is instru

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Index Bias and Current Practices,tion researchers and consumers of segregation studies are habituated to accepting this benchmark for social integration. On reflection, however, it is an unusual point of reference for assessing segregation. For one thing, exact even distribution usually is not logically possible because individuals

集中营

New Options for Understanding and Dealing with Index Bias,tions of popular indices of uneven distribution that are free of bias and take expected values of zero when individuals and households are randomly assigned to residential locations. I accomplish this task by drawing on the difference of means formulations of segregation indices introduced in earlie