Neighborhood income segregation is a widespread phenomenon. We explore its origins by modeling neighborhood selection by native Norwegian households making inter‐neighborhood moves, distinguishing influences of shares of three income groups and the discrepancy between the individual household's income and neighborhood median. We conduct a conditional logit analysis employing 2013–2014 population register data from the Oslo, Norway, metropolitan area.
Reports of citizen complaints of police misconduct often note that officers are rarely disciplined for alleged misconduct. The perception of little officer accountability contributes to widespread distrust of law enforcement in communities of color. This project investigates how race and segregation shape the outcomes of allegations made against the Chicago Police Department (CPD) between 2011 and 2014. We find that complaints by black and Latino citizens and against white officers are less likely to be sustained.
The National Labor Relations Board proposes a regulation establishing that students who perform any services for compensation, including, but not limited to, teaching or research, at a private college or university in connection with their studies are not “employees” within the meaning of Section 2(3) of the National Labor Relations Act.
Two field experiments investigated discrimination in an online mental health care market. The subjects were 908 mental health care providers (MHPs) who advertise for clients on a website through which help-seekers email providers. Both studies measured MHPs’ receptiveness to an ostensibly black or white help-seeker requesting an appointment. In the first study, no racial or gender disparities were observed. However, help-seekers in the second study, who signaled lower education than those in the first, were confronted with significantly lower accessibility overall.
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).
When hundreds of thousands of protesters filled the streets of Hong Kong this summer, central figures reportedly took no selfies, avoided Facebook and Twitter, installed prepaid SIM cards, stuck to secure messaging apps, and used cash instead of rechargeable subway cards or other cashless payments. It is not clear whether this will help them avoid “conspiracy to commit public nuisance” charges, which led to prison sentences for leaders of the 2014 Umbrella movement (including sociologist Kin-man Chan).
ASA speaks with applied sociologist Timothy Ready at the 2016 ASA Annual Meeting on August, 2016, in Seattle, WA. Ready talks about what it means to “do sociology,” how he uses sociology in his work, highlights of his work in the field, the relevance of sociological work to society, and his advice to students interested in entering the field.
Racial disparities persist throughout the employment process, with African Americans experiencing significant barriers compared to whites. This article advances the understanding of racial labor market stratification by bringing new theoretical insights and original data to bear on the ways social networks shape racial disparities in employment opportunities. We develop and articulate two pathways through which networks may perpetuate racial inequality in the labor market: network access and network returns.
Racial stratification is well documented in many spheres of social life. Much stratification research assumes that implicit or explicit bias on the part of institutional gatekeepers produces disparate racial outcomes. Research on status-based expectations provides a good starting point for theoretically understanding racial inequalities. In this context it is understood that race results in differential expectations for performance, producing disparate outcomes.
Corporations gather massive amounts of personal data to predict how individuals will behave so that they can profitably price goods and allocate resources. This article investigates the moral foundations of such increasingly prevalent market practices. I leverage the case of credit scores in car insurance pricing—an early and controversial use of algorithmic prediction in the U.S. consumer economy—to unpack the premise that predictive data are fair to use and to understand the conditions under which people are likely to challenge that moral logic.