Comparative Spatial Segregation Analytics
Comparative Spatial Segregation Analytics
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DOI：
10.1007/s40980-021-00075-w
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发表时间：
2021-01
影响因子：
1.9
通讯作者：
S. Rey;R. Cortes;Elijah Knaap
中科院分区：
文献类型：
--
作者：
S. Rey;R. Cortes;Elijah Knaap
比较隔离分析有可能为城市社会空间动态提供丰富的见解。然而，由于不同的空间背景以及民族、种族和阶级分布，同一时间点上两个或更多城市之间的隔离程度的比较可能会变得复杂。两个城市之间的隔离差异在多大程度上是由于空间结构的差异或构成的差异造成的，仍然是一个悬而未决的问题。本文开发了一个框架来理清空间结构和组成在进行比较隔离分析中的贡献。该方法使用嵌入在 Shapley 分解中的空间显式反事实。我们通过对美国 50 个最大都市统计区的案例研究来说明这一框架。
Comparative segregation analysis holds the potential to provide rich insights into urban socio-spatial dynamics. However, comparisons of the levels of segregation between two, or more, cities at the same point in time can be complicated by different spatial contexts as well as ethnic, racial, and class distributions. The extent to which differences in segregation between two cities is due to differences in spatial structure or to differences in composition remains an open question. This paper develops a framework to disentangle the contributions of spatial structure and composition in carrying out comparative segregation analysis. The approach uses spatially explicit counterfactuals embedded in a Shapley decomposition. We illustrate this framework in a case study of the 50 largest metropolitan statistical areas in the U.S.