African women in polygamous marriages or with alcoholic husbands have a significantly higher risk of being physically abused by their husbands than women in monogamous marriages or women whose husbands don't abuse alcohol, new research shows.
"Why doesn't she just leave?" is a timeworn question about women trapped in relationships with men who physically and/or emotionally abuse them. Economic dependence is clearly part of the story — many women lack the financial means to leave and find themselves trapped by both poverty and abuse.
Lawyers keep the gates of public justice institutions, particularly through their roles in formal procedures like hearings and trials. Yet, it is not clear what lawyers do in such quintessentially legal settings: conclusions from past research are bedeviled by a lack of clear theory and inconsistencies in research design. Conceptualizing litigation work in terms of professional expertise, I conduct a theoretically grounded synthesis of the findings of extant studies of lawyers’ impact on civil case outcomes.
ASA speaks with sociologist Doug Hartmann at the 2016 ASA Annual Meeting on August, 2016, in Seattle, WA. Hartmann 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.
We know men’s violence against women is costly. Yet, we know little about the costs—or benefits—of women’s efforts to end it. This study investigates the temporal dynamics of women’s earnings and petitioning for a Protection from Abuse (PFA) civil restraining order. Women’s earnings might rise or fall at the time of petitioning but quickly return to pre-petitioning levels, a short-term boost or shock; or, petitioning might precipitate a longer-term stall or upward shift in women’s earnings.
The meaning of objectivity in any specific setting reflects historically situated understandings of both science and self. Recently, various scientific fields have confronted growing mistrust about the replicability of findings, and statistical techniques have been deployed to articulate a “crisis of false positives.” In response, epistemic activists have invoked a decidedly economic understanding of scientists’ selves. This has prompted a scientific social movement of proposed reforms, including regulating disclosure of “backstage” research details and enhancing incentives for replication.
Using a reproductive coercion framework, we investigate the role of intimate partner violence (IPV) in pregnancy during the transition to adulthood. We use two types of data from a population-based sample of 867 young women in a Michigan county: a 60-minute survey interview with 2.5 years of weekly follow-up surveys, and semi-structured interviews with a subsample of 40 pregnant women. The semi-structured interviews illustrate the violence women experienced.
Researchers studying income inequality, economic segregation, and other subjects must often rely on grouped data—that is, data in which thousands or millions of observations have been reduced to counts of units by specified income brackets.
As Michael Schultz notes in his very interesting paper (this volume, pp. 52–87), standard model selection criteria, such as the Akaike information criterion (AIC; Akaike 1974), the Bayesian information criterion (BIC; Schwarz 1978), and the minimum description length principle (MDL; Rissanen 1978), are purely empirical criteria in the sense that the score a model receives does not depend on how well the model coheres with background theory. This is unsatisfying because we would like our models to be theoretically plausible, not just empirically successful.
Conventional model selection evaluates models on their ability to represent data accurately, ignoring their dependence on theoretical and methodological assumptions. Drawing on the concept of underdetermination from the philosophy of science, the author argues that uncritical use of methodological assumptions can pose a problem for effective inference. By ignoring the plausibility of assumptions, existing techniques select models that are poor representations of theory and are thus suboptimal for inference.