Publications by authors named "Ryan D Enos"

Does local partisan context influence the adoption of prosocial behavior? Using a nationwide survey of 60,000 adults and geographic data on over 180 million registered voters, we investigate whether neighborhood partisan composition affects a publicly observable and politicized behavior: wearing a mask. We find that Republicans are less likely to wear masks in public as the share of Republicans in their zip codes increases. Democratic mask wearing, however, is unaffected by local partisan context.

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Does contact across social groups influence sociopolitical behavior? This question is among the most studied in the social sciences with deep implications for the harmony of diverse societies. Yet, despite a voluminous body of scholarship, evidence around this question is limited to cross-sectional surveys that only measure short-term consequences of contact or to panel surveys with small samples covering short time periods. Using advances in machine learning that enable large-scale linkages across datasets, we examine the long-term determinants of sociopolitical behavior through an unprecedented individual-level analysis linking contemporary political records to the 1940 U.

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Segregation across social groups is an enduring feature of nearly all human societies and is associated with numerous social maladies. In many countries, reports of growing geographic political polarization raise concerns about the stability of democratic governance. Here, using advances in spatial data computation, we measure individual partisan segregation by calculating the local residential segregation of every registered voter in the United States, creating a spatially weighted measure for more than 180 million individuals.

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Once a fixture of research in the social and behavioral sciences, volunteer subjects are now only rarely used in human subjects research. Yet volunteers are a potentially valuable resource, especially for research conducted online. We argue that online volunteer laboratories are able to produce high-quality data comparable to that from other online pools.

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The effect of intergroup contact has long been a question central to social scientists. As political and technological changes bring increased international migration, understanding intergroup contact is increasingly important to scientific and policy debates. Unfortunately, limitations in causal inference using observational data and the practical inability to experimentally manipulate demographic diversity has limited scholars' ability to address the effects of intergroup contact.

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