On measuring Muslim segregation in urban India

IF 4.2 1区 经济学 Q1 ENVIRONMENTAL STUDIES
Arpit Shah, Anish Sugathan, Naveen Bharathi, Andaleeb Rahman, Amit Garg, Deepak Malghan
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引用次数: 0

Abstract

The spatial segregation of Muslims in urban India is central to their social, economic and political marginalisation. However, the quantitative characterisation of Muslim segregation has suffered from the lack of readily available demographic data at high spatial and temporal resolution. This paper demonstrates the feasibility of accurately quantifying Muslim segregation in urban India using the latest electoral rolls data from Bengaluru (a megapolis of over 13 million residents) and an improved open-source algorithm to identify Muslim names. Our approach provides significant improvements over past efforts in this regard. We introduce two new metrics (diversity and local divergence) to account for substantial intra-city variation in the spatial segregation of Muslims. Our analysis suggests that the threefold ghetto–enclave–mixed taxonomy that the extant literature has quantified for entire towns can be found within large urban agglomerations such as Bengaluru. Our quantitative framework for Muslim segregation helps uncover the complex relationship between segregation and the ghettoisation of Muslims in urban India. Our measurement framework uses publicly available data and can be applied to study segregation patterns across urban India.
关于衡量印度城市穆斯林隔离情况
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来源期刊
Urban Studies
Urban Studies Multiple-
CiteScore
10.50
自引率
8.50%
发文量
150
期刊介绍: Urban Studies was first published in 1964 to provide an international forum of social and economic contributions to the fields of urban and regional planning. Since then, the Journal has expanded to encompass the increasing range of disciplines and approaches that have been brought to bear on urban and regional problems. Contents include original articles, notes and comments, and a comprehensive book review section. Regular contributions are drawn from the fields of economics, planning, political science, statistics, geography, sociology, population studies and public administration.
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