Sociological Methodology最新文献

In addition to overall dispersion, the distributional shape of economic status has attracted growing attention in the inequality literature. Economic polarization is a specific form of distributional change, characterized by a shrinking middle of the distribution and a growing top and bottom, with potentially important and unique social consequences. Building on relative distribution methods and drawing from the literature on job polarization, we develop an approach for analyzing economic polarization at the individual level. Our method has three useful features. First, it offers intuitive and flexible measurement of economic polarization both between and within categories. Second, it helps disentangle two potential sources of economic polarization: compositional change, which involves changes to the allocation of workers across categories, and relative economic status change, which involves changes to the allocation of economic rewards between individuals. Third, it enables researchers to uncover and examine potential heterogeneity in economic polarization, for example across occupations, geographic units, demographic and educational groups, and firms. We demonstrate the utility of our approach through two empirical applications: (1) an analysis of trends in wage polarization between and within occupations and (2) an examination of geographic variation in income polarization.

Sociological approaches to digital and community-engaged research experienced significant innovation in recent years. This article examines developing and implementing a primarily virtual community-driven research (CDR) project with the National Survivors Union, the American national drug-users union, during the COVID-19 pandemic. Relationships between researchers and directly impacted people, such as people who use drugs, face many barriers. These issues were exacerbated during COVID-19 when in-person research decreased while drug-related harms increased. In response, this project modified the CDR model for drug-use research. The CDR model is particularly beneficial for studies with marginalized populations who may mistrust researchers. In CDR, impacted community members are fundamental project drivers. This project's data are based on 29 months of weekly group meetings in National Survivors Union online spaces, group and individual text conversations, phone calls, and shared-document group work. The project co-developed methods for CDR with directly impacted people, including community-initiated research questions, low-threshold methods, collaborative writing strategies, coauthorship practices foregrounding directly impacted perspectives, and multiple dissemination forms. Modified CDR expands sociological methods for digital research, citizen science, and community-engaged research with vulnerable, criminalized groups. This approach may aid inclusive, innovative sociological scholarship and effective public health policy for reducing morbidity and mortality during multiple crises.

Amazon's Mechanical Turk (MTurk) and Prolific are popular online platforms for connecting academic researchers with respondents. A broad literature has sought to assess the extent to which these respondents are representative of the U.S. population in terms of their demographic background, yet no work has assessed the representativeness of their daily lives. The authors provide this analysis by collecting time diaries from 136 MTurk and 156 Prolific respondents, which they compare with diary responses from 468 contemporaneous responses to the American Time Use Survey (ATUS). Responses from MTurk and Prolific respondents include several notable differences relative to ATUS responses, including doing less housework and care work, spending less time traveling, spending more time at home, and spending more time alone. In general, MTurk respondents worked more than ATUS respondents, and Prolific respondents spent more time in leisure. These differences persist even after adjusting for demographic differences. The present findings highlight time use as a potential major source of differences across samples that go beyond demographic differences. Thus, scholars interested in these samples should consider how time use may moderate processes of interest.