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Mobility patterns are associated with experienced income segregation in large US cities
Traditional understanding of urban income segregation is largely based on static coarse-grained residential patterns. However, these do not capture the income segregation experience implied by the rich social interactions that happen in places that may relate to individual choices, opportunities, an...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8324796/ https://www.ncbi.nlm.nih.gov/pubmed/34330916 http://dx.doi.org/10.1038/s41467-021-24899-8 |
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author | Moro, Esteban Calacci, Dan Dong, Xiaowen Pentland, Alex |
author_facet | Moro, Esteban Calacci, Dan Dong, Xiaowen Pentland, Alex |
author_sort | Moro, Esteban |
collection | PubMed |
description | Traditional understanding of urban income segregation is largely based on static coarse-grained residential patterns. However, these do not capture the income segregation experience implied by the rich social interactions that happen in places that may relate to individual choices, opportunities, and mobility behavior. Using a large-scale high-resolution mobility data set of 4.5 million mobile phone users and 1.1 million places in 11 large American cities, we show that income segregation experienced in places and by individuals can differ greatly even within close spatial proximity. To further understand these fine-grained income segregation patterns, we introduce a Schelling extension of a well-known mobility model, and show that experienced income segregation is associated with an individual’s tendency to explore new places (place exploration) as well as places with visitors from different income groups (social exploration). Interestingly, while the latter is more strongly associated with demographic characteristics, the former is more strongly associated with mobility behavioral variables. Our results suggest that mobility behavior plays an important role in experienced income segregation of individuals. To measure this form of income segregation, urban researchers should take into account mobility behavior and not only residential patterns. |
format | Online Article Text |
id | pubmed-8324796 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-83247962021-08-03 Mobility patterns are associated with experienced income segregation in large US cities Moro, Esteban Calacci, Dan Dong, Xiaowen Pentland, Alex Nat Commun Article Traditional understanding of urban income segregation is largely based on static coarse-grained residential patterns. However, these do not capture the income segregation experience implied by the rich social interactions that happen in places that may relate to individual choices, opportunities, and mobility behavior. Using a large-scale high-resolution mobility data set of 4.5 million mobile phone users and 1.1 million places in 11 large American cities, we show that income segregation experienced in places and by individuals can differ greatly even within close spatial proximity. To further understand these fine-grained income segregation patterns, we introduce a Schelling extension of a well-known mobility model, and show that experienced income segregation is associated with an individual’s tendency to explore new places (place exploration) as well as places with visitors from different income groups (social exploration). Interestingly, while the latter is more strongly associated with demographic characteristics, the former is more strongly associated with mobility behavioral variables. Our results suggest that mobility behavior plays an important role in experienced income segregation of individuals. To measure this form of income segregation, urban researchers should take into account mobility behavior and not only residential patterns. Nature Publishing Group UK 2021-07-30 /pmc/articles/PMC8324796/ /pubmed/34330916 http://dx.doi.org/10.1038/s41467-021-24899-8 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Moro, Esteban Calacci, Dan Dong, Xiaowen Pentland, Alex Mobility patterns are associated with experienced income segregation in large US cities |
title | Mobility patterns are associated with experienced income segregation in large US cities |
title_full | Mobility patterns are associated with experienced income segregation in large US cities |
title_fullStr | Mobility patterns are associated with experienced income segregation in large US cities |
title_full_unstemmed | Mobility patterns are associated with experienced income segregation in large US cities |
title_short | Mobility patterns are associated with experienced income segregation in large US cities |
title_sort | mobility patterns are associated with experienced income segregation in large us cities |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8324796/ https://www.ncbi.nlm.nih.gov/pubmed/34330916 http://dx.doi.org/10.1038/s41467-021-24899-8 |
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