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Computational sociology leverages new tools and data sources to expand the scope and scale of sociological inquiry. It’s opening up an exciting frontier for sociologists of every stripe—from theorists and ethnographers to experimentalists and survey researchers. It expands the sociological imagination.
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Women’s opportunities have been profoundly altered over the past century by reductions in the social and structural constraints that limit women’s educational attainment. Do social constraints manifest as a suppressing influence on genetic indicators of potential, and if so, did equalizing opportunity mean equalizing the role of genetics? We address this with three cohort studies: the Wisconsin Longitudinal Study (WLS; birth years 1939 to 1940), the Health and Retirement Study, and the National Longitudinal Study of Adolescent Health (Add Health; birth years 1975 to 1982).
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We study the relationship between inter-class inequality and intergenerational class mobility across 39 countries. Previous research on the relationship between economic inequality and class mobility remains inconclusive, as studies have confounded intra- with between-class economic inequalities. We propose that between-class inequality across multiple dimensions accounts for the inverse relationship between inequality and mobility: the larger the resource distance between classes, the less likely it is that mobility from one to the other will occur.
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Monica Prasad, along with collaborators like Isaac Martin and Ajay Mehrotra (e.g., Martin, Mehrotra, and Prasad 2009), has made fiscal sociology—the sociology of taxation—a thriving part of the discipline. Her first book showed how different national patterns of taxation help explain the variable strength of neoliberalism across nations (Prasad 2006). Her second identified progressive taxation as key to producing both democratized credit and a weak welfare state in the United States (Prasad 2012).
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The short story is that Kieran Healy’s Data Visualization: A Practical Introduction is a gentle introduction to the effective display of social science data using the R package ggplot2. It is beautifully put together, achingly clear, and effective.
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We provide an overview of associations between income inequality and intergenerational mobility in the United States, Canada, and eight European countries. We analyze whether this correlation is observed across and within countries over time. We investigate Great Gatsby curves and perform metaregression analyses based on several papers on this topic. Results suggest that countries with high levels of inequality tend to have lower levels of mobility.
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Music consumption imbues a city's neighborhoods with a character all their own, contributing to a vibrant and dynamic map of urban cultures. Brick‐and‐mortar music retailers remain an important site for this consumption, persisting despite challenges posed by digitization. But the landscape of contemporary cultural consumption has been shaped by urban inequality over time.
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Using a multi‐methods approach, we examine socioeconomic and demographic change in Buffalo, New York's, West Side neighborhood. We do this by performing a systematic case study of the neighborhood analyzing census tract data, crime data, key informant interview data from community leaders and organizational representatives, and content analysis data from local newspaper articles. Results suggest that although the neighborhood has shifted dramatically over the last forty‐five years, the changes have been uneven across the West Side.
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Studies of Latinx–white residential segregation and of Latinx residential attainment consistently report findings consistent with spatial assimilation. Nevertheless, most studies of this theory use statistical models that cannot account for multiple dimensions of neighborhoods that may influence residential attainment. In this article, we test predictions of the spatial assimilation model using discrete choice analyses, a multidimensional model.
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Conventional explanations of police misconduct generally adopt a microlevel focus on deviant officers or a macrolevel focus on the top-down organization of police departments. Between these levels are social networks of misconduct. This study recreates these networks using data on 16,503 complaints and 15,811 police officers over a six-year period in Chicago. We examine individual-level factors associated with receiving a complaint, the basic properties of these misconduct networks, and factors related to officer co-naming in complaints.
