This article uses archival research to explore important differences in the discursive and institutional positioning of Mexican American and African American men during World War II. Through the focal point of the riots that erupted in Los Angeles and other major cities in the summer of 1943, I examine the ways in which black and Mexican "rioters" were imagined in official and popular discourses. Though both groups of youth were often constructed as deviant and subversive, there were also divergences in the ways in which their supposed racial difference was discursively configured.
ASA speaks with sociologist Doug Hartmann at the 2016 ASA Annual Meeting on August, 2016, in Seattle, WA. Hartmann talks about what it means to “do sociology,” how he uses sociology in his work, highlights of his work in the field, the relevance of sociological work to society, and his advice to students interested in entering the field.
Evaluating Charles Tilly’s contributions to the social sciences is not an easy task: “Chuck Tilly was a master of sociological thinking and methodology,” wrote two of his former students when he passed away ten years ago; “But he was sufficiently concerned about getting to the heart and dynamics of questions and topics that he never permitted the blinkers of disciplinary orthodoxy to stand in his way” (Michelson and Wellman 2008).
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.
The diversity of the U.S. urban population has increased dramatically in recent decades, yet the processes through which population diversity may be driving neighborhood change remain insufficiently understood. Building on Claude Fischer's subcultural theory of urbanism and other classic sociological insights, this article makes the case that population diversity shapes the character of place and drives the spatial clustering of artists and art organizations.
Brayden G. King reviews Manufacturing Morals: The Values of Silence in Business School Education by Michel Anteby, Hyper-Organization: Global Organizational Expansion by Patricia Bromley and John W. Meyer, The Vanishing American Corporation: Navigating the Hazards of a New Economy by Gerald F. Davis and The Fracturing of the American Corporate Elite by Mark S. Mizruchi.
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.
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?
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.
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?