Immigration flows and social inequalities reflect increased social and multi-ethnic segregation in contemporary urban Europe. For a better understanding of these processes, the present study investigates the main strengths of the multi-group residential indices, testing sensitivity and reliability under different metropolitan contexts in five European countries. These indices focus on different research dimensions and approach multi-group residential segregation conceptually and mathematically in a different way. A multivariate exploratory data analysis was adopted to classify the observed segregation patterns into a few homogeneous types and to delineate the multivariate relationship between the indices. The results of principal component analysis demonstrate that the indices assessing uniformity and disproportionality of the social groups analysed (H and D) contribute largely to the diversification in today's multi-ethnic communities, clarifying the importance of the dimension of evenness. Our results highlight how segregation is more evident in economically disadvantaged metropolitan regions with high levels of social vulnerability.
Measuring residential segregation in multi‐ethnic and unequal European cities / Benassi, Federico; Naccarato, Alessia; Iglesias‐pascual, Ricardo; Salvati, Luca; Strozza, Salvatore. - In: INTERNATIONAL MIGRATION. - ISSN 1468-2435. - 61:2(2023), pp. 341-361. [10.1111/imig.13018]
Measuring residential segregation in multi‐ethnic and unequal European cities
Federico BenassiPrimo
;Salvatore StrozzaUltimo
2023
Abstract
Immigration flows and social inequalities reflect increased social and multi-ethnic segregation in contemporary urban Europe. For a better understanding of these processes, the present study investigates the main strengths of the multi-group residential indices, testing sensitivity and reliability under different metropolitan contexts in five European countries. These indices focus on different research dimensions and approach multi-group residential segregation conceptually and mathematically in a different way. A multivariate exploratory data analysis was adopted to classify the observed segregation patterns into a few homogeneous types and to delineate the multivariate relationship between the indices. The results of principal component analysis demonstrate that the indices assessing uniformity and disproportionality of the social groups analysed (H and D) contribute largely to the diversification in today's multi-ethnic communities, clarifying the importance of the dimension of evenness. Our results highlight how segregation is more evident in economically disadvantaged metropolitan regions with high levels of social vulnerability.File | Dimensione | Formato | |
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