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Mobility patterns are associated with experienced income segregation in large US cities.
Moro, Esteban; Calacci, Dan; Dong, Xiaowen; Pentland, Alex.
Afiliação
  • Moro E; Media Lab, Massachusetts Institute of Technology, Cambridge, MA, USA. esteban.moroegido@gmail.com.
  • Calacci D; Departamento de Matemáticas & GISC, Universidad Carlos III de Madrid, Leganés, Spain. esteban.moroegido@gmail.com.
  • Dong X; Media Lab, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Pentland A; Media Lab, Massachusetts Institute of Technology, Cambridge, MA, USA.
Nat Commun ; 12(1): 4633, 2021 07 30.
Article em En | MEDLINE | ID: mdl-34330916
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.

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article