RESUMO
In US cities, neighborhoods have long been racially segregated. However, people do not spend all their time in their neighborhoods, and the consequences of residential segregation may be tempered by the contact people have with other racial groups as they traverse the city daily. We examine the extent to which people's regular travel throughout the city is to places "beyond their comfort zone" (BCZ), i.e., to neighborhoods of racial composition different from their own-and why. Based on travel patterns observed in more than 7.2 million devices in the 100 largest US cities, we find that the average trip is to a neighborhood less than half as racially different from the home neighborhood as it could have been given the city. Travel to grocery stores is least likely to be BCZ; travel to gyms and parks, most likely; however, differences are greatest across cities. For the first ~10 km people travel from home, neighborhoods become increasingly more BCZ for every km traveled; beyond that point, whether neighborhoods do so depends strongly on the city. Patterns are substantively similar before and after COVID-19. Our findings suggest that policies encouraging more 15-min travel-that is, to amenities closer to the home-may inadvertently discourage BCZ movement. In addition, promoting use of certain "third places" such as restaurants, bars, and gyms, may help temper the effects of residential segregation, though how much it might do so depends on city-specific conditions.
Assuntos
COVID-19 , Características de Residência , Humanos , COVID-19/epidemiologia , Características da Vizinhança , Cidades , Viagem/estatística & dados numéricos , Estados Unidos , Segregação Social , SARS-CoV-2 , Grupos Raciais/estatística & dados numéricosRESUMO
A common feature of large-scale extreme events, such as pandemics, wildfires, and major storms is that, despite their differences in etiology and duration, they significantly change routine human movement patterns. Such changes, which can be major or minor in size and duration and which differ across contexts, affect both the consequences of the events and the ability of governments to mount effective responses. Based on naturally tracked, anonymized mobility behavior from over 90 million people in the United States, we document these mobility differences in space and over time in six large-scale crises, including wildfires, major tropical storms, winter freeze and pandemics. We introduce a model that effectively captures the high-dimensional heterogeneity in human mobility changes following large-scale extreme events. Across five different metrics and regardless of spatial resolution, the changes in human mobility behavior exhibit a consistent hyperbolic decline, a pattern we characterize as "spatiotemporal decay." When applied to the case of COVID-19, our model also uncovers significant disparities in mobility changes-individuals from wealthy areas not only reduce their mobility at higher rates at the start of the pandemic but also maintain the change longer. Residents from lower-income regions show a faster and greater hyperbolic decay, which we suggest may help account for different COVID-19 rates. Our model represents a powerful tool to understand and forecast mobility patterns post emergency, and thus to help produce more effective responses.
Assuntos
COVID-19 , Migração Humana , Modelos Estatísticos , Desastres Naturais , Pandemias , COVID-19/epidemiologia , Previsões , Migração Humana/tendências , Humanos , Renda , Estações do Ano , Análise Espaço-Temporal , Estados UnidosRESUMO
Influential research on the negative effects of living in a disadvantaged neighborhood assumes that its residents are socially isolated from nonpoor or "mainstream" neighborhoods, but the extent and nature of such isolation remain in question. We develop a test of neighborhood isolation that improves on static measures derived from commonly used census reports by leveraging fine-grained dynamic data on the everyday movement of residents in America's 50 largest cities. We analyze 650 million geocoded Twitter messages to estimate the home locations and travel patterns of almost 400,000 residents over 18 mo. We find surprisingly high consistency across neighborhoods of different race and income characteristics in the average travel distance (radius) and number of neighborhoods traveled to (spread) in the metropolitan region; however, we uncover notable differences in the composition of the neighborhoods visited. Residents of primarily black and Hispanic neighborhoods-whether poor or not-are far less exposed to either nonpoor or white middle-class neighborhoods than residents of primarily white neighborhoods. These large racial differences are notable given recent declines in segregation and the increasing diversity of American cities. We also find that white poor neighborhoods are substantially isolated from nonpoor white neighborhoods. The results suggest that even though residents of disadvantaged neighborhoods travel far and wide, their relative isolation and segregation persist.
Assuntos
Modelos Teóricos , Dinâmica Populacional , Mídias Sociais , População Urbana , Reforma Urbana , Feminino , Humanos , Masculino , Estados UnidosRESUMO
The basic practice of ethnography has essentially remained unchanged in hundreds of years. How has online life changed things? I contrast two transformative inventions, the telephone and the internet, with respect to their impact on fieldwork. I argue that our current era has created entirely new constraints and opportunities for ethnographic research.
RESUMO
Research has made clear that neighbourhood conditions affect racial inequality. We examine how living in minority neighbourhoods affects ease of access to conventional banks versus alternative financial institutions (AFIs) such as check cashers and payday lenders, which some have called predatory. Based on more than 6 million queries, we compute the difference in the time required to walk, drive or take public transport to the nearest bank versus AFI from the middle of every block in each of 19 of the largest cities in the United States. The results suggest that race is strikingly more important than class: even after numerous conditions are accounted for, the AFI is more often closer than the bank in low-poverty racial/ethnic minority neighbourhoods than in high-poverty white ones. Results are driven not by the absence of banks but by the prevalence of AFIs in minority areas. Gaps appear too large to reflect simple differences in preferences.