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  1. Prepare for a Vote: Understanding the Proposed Revision to the ASA Code of Ethics

    At the 2014 Annual Meeting in San Francisco, Executive Officer Sally Hillsman, met with the Committee on Professional Ethics (COPE) and suggested that it was time to revise the Code of Ethics. Revisions were last made to the Code 20 years ago, and a great deal of change had taken place. Regulatory and technological advances have had striking impacts on the field. At the time, the Department of Health and Human Services was about to announce changes to The Common Rule, which governs the vast majority of human subjects research efforts.

  2. ASA Signs on to Letter Supporting Federal Data Sources

    The ASA signed on to a letter expressing our strong support for the critical Federal data sources that inform and strengthen our nation’s world-leading economic, educational, democratic and civic institutions and successes. Our Federal statistical and data systems provide information that is uniquely accurate, objective, relevant, timely, and accessible. 

  3. What’s the Harm? The Coverage of Ethics and Harm Avoidance in Research Methods Textbooks

    Methods textbooks play a role in socializing a new generation of researchers about ethical research. How do undergraduate social research methods textbooks portray harm, its prevalence, and ways to mitigate harm to participants? We conducted a content analysis of ethics chapters in the 18 highest-selling undergraduate textbooks used in sociology research methods courses in the United States and Canada in 2013. We found that experiments are portrayed as the research design most likely to harm participants.
  4. Fuck Nuance

    Nuance is not a virtue of good sociological theory. Although often demanded and superficially attractive, nuance inhibits the abstraction on which good theory depends. I describe three “nuance traps” common in sociology and show why they should be avoided on grounds of principle, aesthetics, and strategy. The argument is made without prejudice to the substantive heterogeneity of the discipline.
  5. What is Critical Realism? And Why Should You Care?

    Critical realism (CR) is a philosophical system developed by the Indo-British philosopher, Roy Bhaskar, in collaboration with a number of British social theorists, including Margaret Archer, Mervyn Hartwig, Tony Lawson, Alan Norrie, and Andrew Sayer. It has a journal, a book series, an association, an annual meeting and, in short, all the usual trappings of an intellectual movement. The movement is centered in the UK but has followers throughout Europe, Asia, the Americas, and the Antipodes.

  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. Why Liberals and Atheists Are More Intelligent

    The origin of values and preferences is an unresolved theoretical question in behavioral and social sciences.

  8. Limitations of Design-based Causal Inference and A/B Testing under Arbitrary and Network Interference

    Randomized experiments on a network often involve interference between connected units, namely, a situation in which an individual’s treatment can affect the response of another individual. Current approaches to deal with interference, in theory and in practice, often make restrictive assumptions on its structure—for instance, assuming that interference is local—even when using otherwise nonparametric inference strategies.
  9. Comment: Evidence, Plausibility, and Model Selection

    In his article, Michael Schultz examines the practice of model selection in sociological research. Model selection is often carried out by means of classical hypothesis tests. A fundamental problem with this practice is that these tests do not give a measure of evidence. For example, if we test the null hypothesis β = 0 against the alternative hypothesis β ≠ 0, what is the largest p value that can be regarded as strong evidence against the null hypothesis? What is the largest p value that can be regarded as any kind of evidence against the null hypothesis?
  10. 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.