Urban segregation is a widespread phenomenon with profound social implications, and one that presents difficult measurement challenges. Segregation indexes may be affected by scale or zoning biases of the modifiable areal unit problem (MAUP). In this article, we develop a methodology that relies on spatial clustering algorithms to simultaneously cope with both kinds of MAUP biases, and we test it with complete census data for most Chilean cities. We find a robust correlation between segregation and city size, contesting previous claims about the spuriousness of this relationship. We also show that socioeconomic polarization is a widespread phenomenon in Chile and that it is not just a problem of disadvantaged groups’ concentration. Based on these results, we suggest that area-based desegregation policies should be generally reinforced, and complemented in big Chilean cities with housing-mix policies. We argue that using spatially unbiased segregation indexes could improve comparative urban studies.

中文翻译：

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探索城市规模与居民隔离之间的相关性：比较智利城市与空间无偏指数

城市隔离是一种广泛的现象，具有深远的社会影响，并且是衡量困难的挑战。隔离指数可能会受到可修改面积单位问题（MAUP）的规模或分区偏差的影响。在本文中，我们开发了一种方法，该方法依赖于空间聚类算法来同时应对两种MAUP偏差，并针对大多数智利城市使用完整的人口普查数据对其进行了测试。我们发现种族隔离与城市规模之间存在稳固的相关性，这与先前关于这种关系的虚假性的说法不符。我们还表明，社会经济两极分化在智利是一种普遍现象，而不仅仅是弱势群体集中的问题。根据这些结果，我们建议总体上应加强基于区域的种族隔离政策，并在智利大城市实施了住房混合政策。我们认为，使用空间上无偏见的隔离指数可以改善比较城市研究。