Racial Segregation in Everyday Mobility Patterns: Disentangling the Effect of Travel Time

Abstract

Nascent research documents that U.S. racial segregation is not merely a residential phenomenon but is present in everyday mobility patterns. Better understanding the causes of mobility-based segregation requires disentangling the spatial macrosegregation, which constitutes an obvious confounding factor. In this work, the author analyzes big data on everyday visits between 270 million neighborhood dyads to estimate the effect of neighborhood racial composition on mobility patterns, net of driving, walking, and public transportation travel time. Matching on these travel times, the author finds that residents of Black and Hispanic neighborhoods visit White neighborhoods only slightly less than they visit other Black and Hispanic neighborhoods. Distinctly, residents of White neighborhoods are far less likely to visit non-White neighborhoods than other White neighborhoods, even net of travel time. The author finds that this travel time–adjusted visit homophily among White neighborhoods is greater in commuting zones where White neighborhoods are situated closer to non-White neighborhoods.

How people are exposed to neighborhoods racially different from their own

“…The models make clear that, regardless of POI category, predicted dissimilarity is lower in visited neighborhoods than in those that could have been visited—i.e., visits exhibit preference for similar neighborhoods (see also refs. 10 – 14 ). Moreover, the observed preference for similarity is strongest when visiting grocery stores and weakest when visiting gyms.…”

“…While traditional studies have focused on segregation by residence, new research has examined segregation by residents’ everyday movements ( 8 – 10 ). Studies using geotracking cellular phone data have found that everyday travel for work, leisure, and other activities is still highly segregated ( 10 – 14 ), not only by race but also by income ( 15 – 18 ). How best to conceptualize segregation by movement and why it remains pervasive remain open questions.…”

“…Rather than focusing on the presence or absence of contact between pairs of groups (e.g., ref. 14 ), collapsing racial groups into general categories such as white/nonwhite (e.g., ref. 12 ), or ignoring differences among neighborhoods that have a given racial majority (e.g., ref.…”

Durable Change in U.S. Urban Mobility Networks, 2019–2022

“…Although COVID-19 remained ever present during this time period, economic issues, such as inflation, emerged in 2022 that may be important for understanding observed changes in mobility. Future work should engage with these important questions, looking to study alternative sociodemographic distributions within census tracts or apply community detection and regionalization methods to detect alternative spatial scales of mobility dissimilarity (Chodrow 2017; Huang et al 2022; Vachuska 2023).…”

“…Where people move throughout the day defines the social patterning of exposures to everything from air pollution (Brazil 2022;Ma et al 2020) through crime (Graif et al 2021;Graif, Lungeanu, and Yetter 2017;Levy, Phillips, and Sampson 2020), and economic opportunity (Covington 2018;Ruef and Grigoryeva 2020;Sugie and Lens 2017). Furthermore, daily mobility is also closely linked to residential segregation (Candipan et al 2021;Phillips et al 2021;Vachuska 2023;Wang et al 2018), and this intersection places those who are disadvantaged both in their residential context and movement at a compounded disadvantage (Krivo et al 2013;Levy et al 2020). Given the societal implications of changes in travel within cities, this article investigates how the shifts that emerged at the beginning of the pandemic in 2020 (Gyorgy et al 2023;Marlow et al 2021) evolved with pandemic conditions.…”