Human mobility networks reveal increased segregation in large cities.

A long-standing expectation is that large, dense and cosmopolitan areas support socioeconomic mixing and exposure among diverse individuals1-6. Assessing this hypothesis has been difficult because previous measures of socioeconomic mixing have relied on static residential housing data rather than real-life exposures among people at work, in places of leisure and in home neighbourhoods7,8. Here we develop a measure of exposure segregation that captures the socioeconomic diversity of these everyday encounters. Using mobile phone mobility data to represent 1.6 billion real-world exposures among 9.6 million people in the United States, we measure exposure segregation across 382 metropolitan statistical areas (MSAs) and 2,829 counties. We find that exposure segregation is 67% higher in the ten largest MSAs than in small MSAs with fewer than 100,000 residents. This means that, contrary to expectations, residents of large cosmopolitan areas have less exposure to a socioeconomically diverse range of individuals. Second, we find that the increased socioeconomic segregation in large cities arises because they offer a greater choice of differentiated spaces targeted to specific socioeconomic groups. Third, we find that this segregation-increasing effect is countered when a city's hubs (such as shopping centres) are positioned to bridge diverse neighbourhoods and therefore attract people of all socioeconomic statuses. Our findings challenge a long-standing conjecture in human geography and highlight how urban design can both prevent and facilitate encounters among diverse individuals.

Mobility network models of COVID-19 explain inequities and inform reopening.

The coronavirus disease 2019 (COVID-19) pandemic markedly changed human mobility patterns, necessitating epidemiological models that can capture the effects of these changes in mobility on the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)1. Here we introduce a metapopulation susceptible-exposed-infectious-removed (SEIR) model that integrates fine-grained, dynamic mobility networks to simulate the spread of SARS-CoV-2 in ten of the largest US metropolitan areas. Our mobility networks are derived from mobile phone data and map the hourly movements of 98 million people from neighbourhoods (or census block groups) to points of interest such as restaurants and religious establishments, connecting 56,945 census block groups to 552,758 points of interest with 5.4 billion hourly edges. We show that by integrating these networks, a relatively simple SEIR model can accurately fit the real case trajectory, despite substantial changes in the behaviour of the population over time. Our model predicts that a small minority of 'superspreader' points of interest account for a large majority of the infections, and that restricting the maximum occupancy at each point of interest is more effective than uniformly reducing mobility. Our model also correctly predicts higher infection rates among disadvantaged racial and socioeconomic groups2-8 solely as the result of differences in mobility: we find that disadvantaged groups have not been able to reduce their mobility as sharply, and that the points of interest that they visit are more crowded and are therefore associated with higher risk. By capturing who is infected at which locations, our model supports detailed analyses that can inform more-effective and equitable policy responses to COVID-19.

The intergenerational sources of the U-turn in gender segregation.

In the early 1970s, the balkanization of the US labor market into "men's occupations" and "women's occupations" began to unravel, as women entered the professions and other male-typed sectors in record numbers. This decline in gender segregation continued on for several decades but then suddenly stalled at the turn of the century and shows no signs of resuming. Although the stall is itself undisputed, its sources remain unclear. Using nearly a half-century of data from the General Social Survey, we show that a resurgence in segregation-inducing forms of intergenerational transmission stands behind the recent stall. Far from serving as impartial conduits, fathers are now disproportionately conveying male-typed occupations to their sons, whereas mothers are effectively gender-neutral in their transmission outcomes. This segregative turn among fathers accounts for 47% of the stall in the gender segregation trend (between 2000 and 2018), while the earlier integrative turn among fathers accounts for 34% of the initial downturn in segregation (between 1972 and 1999). It follows that a U-turn in intergenerational processes lies behind the U-turn in gender segregation.

A post-liberal theory of stratification.

The iconic 'liberal theory' of stratification fails to attend to the many types of downward mobility and wage loss generated by late-industrial stratification systems. Although the liberal theory and its close cousins assume that loss and failure will be interpreted in individualistic terms, recent developments suggest instead that they are generating solidary groups that are increasingly locked into zero-sum contest and successfully mobilized by politicians and other norm entrepreneurs. These developments imply a Marxisant future for late-industrial inequality that bears scant resemblance to the highly individualized, unstructured, and non-conflictual stratification system envisaged by the liberal theory. We outline a new post-liberal theory of stratification that better captures the forces making for change and resistance in late-industrial societies.

A New Infrastructure for Monitoring Social Mobility in the United States.

The country's capacity to monitor trends in social mobility has languished since the last major survey on U.S. social mobility was fielded in 1973. It is accordingly difficult to evaluate recent concerns that social mobility may be declining or to develop mobility policy that is adequately informed by evidence. This article presents a new initiative, dubbed the American Opportunity Study (AOS), that would allow the country to monitor social mobility efficiently and with great accuracy. The AOS entails developing the country's capacity to link records across decennial censuses, the American Community Survey, and administrative sources. If an AOS of this sort were assembled, it would open up new fields of social science inquiry; increase opportunities for evidence-based policy on poverty, mobility, child development, and labor markets; and otherwise constitute a new social science resource with much reach and impact.

The American Opportunity Study: A New Infrastructure for Monitoring Outcomes, Evaluating Policy, and Advancing Basic Science.

The American Opportunity Study is an ongoing initiative to build the country's capacity to access and analyze linked administrative data. It is best viewed as a population-level scaffolding on which other administrative data can then be hung. This scaffolding, if used as a stand-alone resource, will allow for long-run analyses of fundamental population and labor market processes. If combined with data from other sources, it will allow for long-run program evaluation and other experimental and quasi-experimental analyses. We discuss the current status of the American Opportunity Study, its potential to advance the field, remaining obstacles that must be overcome to build it, and how it can work within the guidelines suggested by the Commission on Evidence-Based Policymaking.

The fading American dream: Trends in absolute income mobility since 1940.

We estimated rates of "absolute income mobility"-the fraction of children who earn more than their parents-by combining data from U.S. Census and Current Population Survey cross sections with panel data from de-identified tax records. We found that rates of absolute mobility have fallen from approximately 90% for children born in 1940 to 50% for children born in the 1980s. Increasing Gross Domestic Product (GDP) growth rates alone cannot restore absolute mobility to the rates experienced by children born in the 1940s. However, distributing current GDP growth more equally across income groups as in the 1940 birth cohort would reverse more than 70% of the decline in mobility. These results imply that reviving the "American dream" of high rates of absolute mobility would require economic growth that is shared more broadly across the income distribution.

Microclass mobility: social reproduction in four countries.

In the sociological literature on social mobility, the long-standing convention has been to assume that intergenerational reproduction takes one of two forms: a categorical form that has parents passing on a big-class position to their children or a gradational form that has parents passing on their socioeconomic standing. These approaches ignore in their own ways the important role that occupations play in transferring opportunities from one generation to the next. In new analyses of nationally representative data from the United States, Sweden, Germany, and Japan, the authors show that (a) occupations are an important conduit for social reproduction, (b) the most extreme rigidities in the mobility regime are only revealed when analyses are carried out at the occupational level, and (c) much of what shows up as big-class reproduction in conventional mobility analyses is in fact occupational reproduction in disguise.