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  1. We Ran 9 Billion Regressions: Eliminating False Positives through Computational Model Robustness

    False positive findings are a growing problem in many research literatures. We argue that excessive false positives often stem from model uncertainty. There are many plausible ways of specifying a regression model, but researchers typically report only a few preferred estimates. This raises the concern that such research reveals only a small fraction of the possible results and may easily lead to nonrobust, false positive conclusions. It is often unclear how much the results are driven by model specification and how much the results would change if a different plausible model were used.
  2. Estimating Heterogeneous Treatment Effects with Observational Data

    Individuals differ not only in their background characteristics but also in how they respond to a particular treatment, intervention, or stimulation. In particular, treatment effects may vary systematically by the propensity for treatment. In this paper, we discuss a practical approach to studying heterogeneous treatment effects as a function of the treatment propensity, under the same assumption commonly underlying regression analysis: ignorability.

  3. Inequality in Reading and Math Skills Forms Mainly before Kindergarten: A Replication, and Partial Correction, of “Are Schools the Great Equalizer?”

    When do children become unequal in reading and math skills? Some research claims that inequality grows mainly before school begins. Some research claims that schools cause inequality to grow. And some research—including the 2004 study ‘‘Are Schools the Great Equalizer?’’—claims that inequality grows mainly during summer vacations. Unfortunately, the test scores used in the Great Equalizer study suffered from a measurement artifact that exaggerated estimates of inequality growth. In addition, the Great Equalizer study is dated and its participants are no longer school-aged.
  4. Visualizing Income Inequality and Mobility Together

    Research and public conversations about income inequality and intergenerational mobility will benefit from a new approach that jointly visualizes these two measures. The new mobility table proposed addresses this concern by scaling each quintile by the spread of income it represents. Implications of this approach for future analyses of inequality and mobility are discussed.
  5. Featured Essay: Lost and Saved . . . Again: The Moral Panic about the Loss of Community Takes Hold of Social Media

    Why does every generation believe that relationships were stronger and community better in the recent past? Lamenting about the loss of community, based on a selective perception of the present and an idealization of ‘‘traditional community,’’ dims awareness of powerful inequalities and cleavages that have always pervaded human society and favors deterministic models over a nuanced understanding of how network affordances contribute to different outcomes. Taylor Dotson’s (2017) recent book proposes a broader timeline for the demise of community.
  6. Perceived Unfair Treatment by Police, Race, and Telomere Length: A Nashville Community-based Sample of Black and White Men

    Police maltreatment, whether experienced personally or indirectly through one’s family or friends, represents a structurally rooted public health problem that disproportionately affects minorities. Researchers, however, know little about the physiological mechanisms connecting unfair treatment by police (UTBP) to poor health. Shortened telomeres due to exposure to this stressor represent one plausible mechanism.
  7. Correction

    In the trends piece, “Taking a Knee” (Summer 2018), two figures had labeling errors. Please see with corrected figures here or visit contexts.org/articles/nfl for the full article with corrections.
  8. Response to Morgan: On the Role of Status Threat and Material Interests in the 2016 Election

    I am delighted to have the opportunity to respond to Morgan’s article, which is a critique of my recent publication (Mutz 2018). I will restrict my response to matters concerning the data and analysis, excluding issues such as whether the journal PNAS is appropriately named (Morgan this issue:3) as well as Morgan’s views about how this work was covered in various media outlets (Morgan this issue:3–6). These issues are less important than whether material self-interest or status threat motivated Trump supporters.

  9. A Novel Measure of Moral Boundaries: Testing Perceived In-group/Out-group Value Differences in a Midwestern Sample

    The literature on group differences and social identities has long assumed that value judgments about groups constitute a basic form of social categorization. However, little research has empirically investigated how values unite or divide social groups. The authors seek to address this gap by developing a novel measure of group values: third-order beliefs about in- and out-group members, building on Schwartz value theory. The authors demonstrate that their new measure is a promising empirical tool for quantifying previously abstract social boundaries.
  10. Share, Show, and Tell: Group Discussion or Simulations Versus Lecture Teaching Strategies in a Research Methods Course

    Impacts of incorporating active learning pedagogies into a lecture-based course were examined among 266 students across nine research methods course sections taught by one instructor at a large public university. Pedagogies evaluated include lecture only, lecture with small group discussions, and lecture with simulations. Although lecture-simulations sections outperformed lecture-only sections on one outcome measure, few performance differences appeared between lecture-only and alternative groups.