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  1. The Status–Health Paradox: Organizational Context, Stress Exposure, and Well-being in the Legal Profession

    Prior research evaluates the health effects of higher status attainment by analyzing highly similar individuals whose circumstances differ after some experience a “status boost.” Advancing that research, we assess health differences across organizational contexts among two national samples of lawyers who were admitted to the bar in the same year in their respective countries. We find that higher-status lawyers in large firms report more depression than lower-status lawyers, poorer health in the American survey, and no health advantage in Canada.
  2. Invisible Inequality Among “Wounded Warriors”

    The term “wounded warriors,” both a socially designated status and an official medical classification, creates divisions among service members.

  3. When the Personal is Political—and Infectious

    Privilege, distrust, individual choice, and parental care all factor into vaccine resistance, but the consequences are anything but personal.

  4. The Struggle to Save Abortion Care

    by Carole Joffe, Summer 2018 Contexts

  5. The Emergence of Statistical Objectivity: Changing Ideas of Epistemic Vice and Virtue in Science

    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.
  6. From the Bookshelf of a Sociologist of Diagnosis: A Review Essay

    The present essay will take readers through the bookshelf of this sociologist of diagnosis. It will demonstrate the wide-reaching topics that I consider relevant to the sociologist who considers diagnosis as a social object and also as a point of convergence where doctor and lay person encounter one another, where authority is exercised, health care is organized, political priorities are established, and conflict is enacted.

  7. Understanding Racial-ethnic Disparities in Health: Sociological Contributions

    This article provides an overview of the contribution of sociologists to the study of racial and ethnic inequalities in health in the United States. It argues that sociologists have made four principal contributions. First, they have challenged and problematized the biological understanding of race. Second, they have emphasized the primacy of social structure and context as determinants of racial differences in disease. Third, they have contributed to our understanding of the multiple ways in which racism affects health.

  8. Mechanisms Linking Social Ties and Support to Physical and Mental Health

    Over the past 30 years investigators have called repeatedly for research on the mechanisms through which social relationships and social support improve physical and psychological well-being, both directly and as stress buffers. I describe seven possible mechanisms: social influence/social comparison, social control, role-based purpose and meaning (mattering), self-esteem, sense of control, belonging and companionship, and perceived support availability. Stress-buffering processes also involve these mechanisms.

  9. Estimating Income Statistics from Grouped Data: Mean-constrained Integration over Brackets

    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.
  10. Causal Inference with Networked Treatment Diffusion

    Treatment interference (i.e., one unit’s potential outcomes depend on other units’ treatment) is prevalent in social settings. Ignoring treatment interference can lead to biased estimates of treatment effects and incorrect statistical inferences. Some recent studies have started to incorporate treatment interference into causal inference. But treatment interference is often assumed to follow a simple structure (e.g., treatment interference exists only within groups) or measured in a simplistic way (e.g., only based on the number of treated friends).