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This study examines whether working with a broker increases or reduces the payment received for the last client among female sex workers. Building on research on the informal economy and sex work, we formulate a positive embeddedness hypothesis, expecting a positive association, and an exploitation hypothesis, expecting a negative association. We analyze a large survey combined with intensive interview data on female sex workers in Andhra Pradesh, India. These data uniquely distinguish between the amount the sex worker actually received and the amount the client paid.
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Recent scholarship highlights the importance of public discourse for the mobilization and impact of social movements, but it neglects how cultural products may shift discourse and thereby influence mobilization and political outcomes. This study investigates how activism against hydraulic fracturing ("fracking") utilized cultural artifacts to influence public perceptions and effect change. A systematic analysis of Internet search data, social media postings, and newspaper articles allows us to identify how the documentary Gasland reshaped public discourse.
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A growing trend in the criminal justice system is the move toward problem-solving courts, including mental health courts. Using case studies of two mental health courts in a West Coast city, this article seeks to explore how mental health courts may operate by reducing stigma among clients. From observations of the court process in mental health courts and qualitative interviews with mental health court professional staff and mental health court clients, ritual process emerged as a powerful theme that underscores the management of social stigma.
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Social capital theorists claim that belonging to a densely knit social network creates a shared identity, mutually beneficial exchange, trust, and a sense of belonging in that group. Taken together with the empirical research on the importance of social support and social integration for individuals’ well-being, there is reason to expect that the density of one’s personal social network should be positively related to well-being.
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Although sequence analysis has now become a widespread approach in the social sciences, several strategies have been developed to handle the specific issue of multidimensional sequences. These strategies have distinct characteristics related to the way they explicitly emphasize multidimensionality, interdependence, and parsimony.
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"Big data" in the form of unstructured text pose challenges and opportunities to social scientists committed to advancing research frontiers. Because machine-based and human-centric approaches to content analysis have different strengths for extracting information from unstructured text, the authors argue for a collaborative, hybrid approach that combines their comparative advantages.
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Context effects on survey response, caused by the unobserved interaction between beliefs stored in personal memory and triggers generated by the structure of the survey instrument, are a pervasive challenge to survey research. The authors argue that randomized survey experiments on representative samples, when paired with facilitative primes, can enable researchers to model selection into variable context effects, revealing heterogeneity at the population level.
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We argue that the mismatch between data and analytical methods, along with common practices for dealing with "messy" data, can lead to inaccurate conclusions. Specifically, using previously published data on racial bias and culture of honor, we show that manifest effects, and therefore theoretical conclusions, are highly dependent on how researchers decide to handle extreme scores and nonlinearities when data are analyzed with traditional approaches.
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Recent methodological debates in sociology have focused on how data and analyses might be made more open and accessible, how the process of theorizing and knowledge production might be made more explicit, and how developing means of visualization can help address these issues. In ethnography, where scholars from various traditions do not necessarily share basic epistemological assumptions about the research enterprise with either their quantitative colleagues or one another, these issues are particularly complex.
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Statistical analysis of mobility tables has long played a pivotal role in comparative stratification research. This article proposes a shrinkage estimator of the log-odds ratio for comparing mobility tables. Building on an empirical Bayes framework, the shrinkage estimator improves estimation efficiency by "borrowing strength" across multiple tables while placing no restrictions on the pattern of association within tables.
