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  1. Contexts: Trump365

    Contexts
    Winter 2018, Vol. 17, No. 1

    Features include "After Charlottesville", "Ethnonationalism and the Rise of Donald Trump", "Trump’s Immigration Attacks, in Brief", "Making Protest Great Again", "Emasculation, Conservatism, and the 2016 Election", "Maintaining Supremacy by Blocking Affirmative Action", and "The Algorithmic Rise of the “Alt-Right."

  2. Educational Inequalities in Depression: Do Labor Markets Matter?

    There is little theoretical understanding of why educational inequalities in depression are larger in some countries than in others. The current research tries to fill this gap by focusing on the way in which important labor market processes, specifically upgrading and polarization, affect the relationship between education and depression. Analyses are based on a subsample, aged between 20 and 65, in 26 countries participating in the European Social Survey (N = 56,881) in 2006, 2012, and 2014.
  3. Not in Your Backyard! Organizational Structure, Partisanship, and the Mobilization of Nonbeneficiary Constituents against “Fracking” in Illinois, 2013–2014

    In the interest of enlarging their constituencies, social movements often broaden mobilization efforts beyond the directly aggrieved, beneficiary populations. The authors examine this process through an analysis of a movement against unconventional oil and gas development (UOGD or “fracking”) in Illinois. Using data on more than 37,000 public comments submitted during a regulatory review of fracking, the authors examine the composition of the antifracking movement’s constituency.
  4. Transnational Social Movement Organizations and Counter-Hegemonic Struggles Today

    World-systems analysts have drawn our attention to the importance of the long-standing worldwide struggles of subaltern groups to defend their livelihoods and address fundamental conflicts of our times. Climate change, financial volatility, and rising inequality are exposing the existential threats the global capitalist system poses to growing numbers—many of whom once enjoyed some of its benefits. These urgent challenges create possibilities for social movements to attract more widespread support for alternatives to global capitalism.
  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. The Evolution of Gender Segregation over the Life Course

    We propose a measure of gender segregation over the life course that includes differences between women and men in occupational allocation, degree of time involvement in paid work, and their participation in different forms of economic activity and inactivity, such as paid work, homemaking, and retirement. We pool 21 Labour Force Surveys for the United Kingdom to measure, compare, and add up these various forms of segregation—occupational, time-related, and economic—from 1993 to 2013 (n = 1,815,482).
  7. Do‐It‐Yourself Urban Design: The Social Practice of Informal “Improvement” Through Unauthorized Alteration

    There are numerous ways in which people make illegal or unauthorized alterations to urban space.

  8. The Problem of Underdetermination in Model Selection

    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.
  9. Comment: The Inferential Information Criterion from a Bayesian Point of View

    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.
  10. 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.