The Status of Sociology within the Academy: Where We Are, Why We’re There, and How to Change It

We present data from a survey of deans at colleges and universities throughout the USA on the relative status of disciplines. Findings indicate that the relative status of Sociology within the academy is low, although there are several specific areas of high status—namely, concerning community involvement and engagement. Our analyses also investigate which areas of activity are most closely associated with the overall prestige of disciplines. Findings indicate that research-oriented activities are the most influential, while student-oriented activities have a more ambivalent association with status. Based on those findings, we offer suggestions for raising the status of the discipline, based on the cultivation of natural synergies linking research, community engagement, student training, and focusing on the benefits of establishing social science research centers associated with Sociology departments.     

Mining for Conflict and Staking Claims: Contested Illness at the Tar Creek Superfund Site

Drawing from extensive fieldwork and document analysis, we examine environmental illness claims in Oklahoma's Tar Creek basin, one of the Environmental Protection Agency's (EPA) premier Superfund sites. Our findings indicate that contested illness in the Tar Creek Superfund site differed from typical cases in that the links between high lead exposures and permanent neurological damage were thoroughly and unequivocally documented. But, despite the certainty of these linkages, residents remained embroiled in controversy and they encountered obstacles in obtaining diagnoses, treatment, and compensation. The resultant environmental dispute took two forms: conflict between residents and EPA officials over the adequacy of the agency's remediation project and conflict among residents over ultimate responsibility for children's lead exposures and consequent learning disabilities.     

Observations on the effect of the prior distribution on the predictive distribution in Bayesian inferences

Typically, in the brief discussion of Bayesian inferential methods presented at the beginning of calculus-based undergraduate or graduate mathematical statistics courses, little attention is paid to the process of choosing the parameter value(s) for the prior distribution. Even less attention is paid to the impact of these choices on the predictive distribution of the data. Reasons for this include that the posterior can be found by ignoring the predictive distribution thereby streamlining the derivation of the posterior and/or that computer software can be used to find the posterior distribution. In this paper, the binomial, negative-binomial and Poisson distributions along with their conjugate beta and gamma priors are utilized to obtain the resulting predictive distributions. It is then demonstrated that specific choices of the parameters of the priors can lead to predictive distributions with properties that might be surprising to a non-expert user of Bayesian methods.