American Sociological Association



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  1. 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.
  2. 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?
  3. Comment: Bayes, Model Uncertainty, and Learning from Data

    The problem of model uncertainty is a fundamental applied challenge in quantitative sociology. The authors’ language of false positives is reminiscent of Bonferroni adjustments and the frequentist analysis of multiple independent comparisons, but the distinct problem of model uncertainty has been fully formalized from a Bayesian perspective.
  4. Comment: Some Challenges When Estimating the Impact of Model Uncertainty on Coefficient Instability

    I once had a colleague who knew that inequality was related to an important dependent variable. This colleague knew many other things, but I focus on inequality as an example. It was difficult for my colleague to know just how to operationalize inequality. Should it be the percentage of income held by the top 10 percent, top 5 percent, or top 1 percent of the population? Should it be based on the ratio of median black income to median white income, or should it be the log of that ratio? Should it be based on the Gini index, or perhaps the Theil index would be better?
  5. 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.
  6. How School Socioeconomic Status Affects Achievement Growth across School Transitions in Early Educational Careers

    Our study investigates how changing socioeconomic status (SES) composition, measured as percentage free and reduced priced lunch (FRL), affects students’ math achievement growth after the transition to middle school. Using the life course framework of cumulative advantage, we investigate how timing, individual FRL status, and legacy effects of a student’s elementary school SES composition each affect a student’s math achievement growth. We advance research on school transitions by considering how changing contexts affect achievement growth across school transitions.
  7. What’s Taking You So Long? Examining the Effects of Social Class on Completing a Bachelor’s Degree in Four Years

    Despite improved access in expanded postsecondary systems, the great majority of bachelor’s degree graduates are taking considerably longer than the allotted four years to complete their four-year degrees. Taking longer to finish one’s BA has become so pervasive in the United States that it has become the norm for official statistics released by the Department of Education to report graduation rates across a six-year window.
  8. Social Networks and Educational Attainment among Adolescents Experiencing Pregnancy

    Pregnant adolescents are a population at risk for dropout and have been found to complete fewer years of education than peers. Pregnant girls’ social experience in school may be a factor in their likelihood to persist, as social integration is thought to buffer dropout risk. Pregnant teens have been found to have fewer friends than their peers, but the academic ramifications of these social differences have yet to be studied. In this study the author examines whether friendship networks are associated with the relationship between adolescent pregnancy and educational attainment.

  9. Visualizing Bring-backs

    The figure plots the number of articles that have attempted to “bring” something “back in” in the social sciences by publication year and number of citations. Andrew Abbott, taking a (pessimistic) sociology of knowledge perspective, identified this tendency—beginning with Homans’s classic article “Bringing Men Back in”—as emblematic of the tendency to rediscover old ideas in sociology. The plot shows that “bring-backs” did not become a common yearly occurrence until the mid to late 1990s but are now relatively frequent.
  10. Text Analysis with JSTOR Archives

    I provide a visual representation of keyword trends and authorship for two flagship sociology journals using data from JSTOR’s Data for Research repository. While text data have accompanied the digital spread of information, it remains inaccessible to researchers unfamiliar with the required preprocessing. The visualization and accompanying code encourage widespread use of this source of data in the social sciences.