Myth,allegiances, and the study of social control

That sociology subscribes to certain popular myths and has aligned itself with the welfare of some groups over others complicates research into social control. This is especially so when the research deals with stereotypes and their effects on differential legal treatment. That the discipline has historically taken sides regarding certain commonly held stereotypes and been supportive of certain groups, means that findings that challenge those stereotypes or that are viewed as detrimental to the supported groups are brought into question. Our research on a regulatory mechanism of social control—the Black Book, a list of persons excluded from licensed gaming in Nevada because of their perceived threat to the industry—is illustrative of these complications. Our findings that the Black Book is largely symbolic and is applied discriminatorily challenge not only beliefs in its efficacy but certain myths and allegiances within sociology. That a group sociologically identified with the problem was discriminated against, and that a well-protected group elicited preferential treatment at the hands of regulators who identify with them have been particularly problematic for the acceptance of the findings. We argue here that debunking myth and value neutrality are essential to scientific endeavor and should override such disciplinary tendencies toward the tolerance and protection of some groups over others. Her research has dealt with aspects of culture, organized crime, and social elites. She is currently working on a book on high society and thoroughbred racing. His publications have dealt with issues of labeling and secondary deviation, the role of stereotypes in the legal process, and the legal reaction to corporate crime.     

Generalized Laplacian approximations in Bayesian inference

This paper presents a new Laplacian approximation to the posterior density of η = g(θ). It has a simpler analytical form than that described by Leonard et al. (1989). The approximation derived by Leonard et al. requires a conditional information matrix R_η to be positive definite for every fixed η. However, in many cases, not all R_η are positive definite. In such cases, the computations of their approximations fail, since the approximation cannot be normalized. However, the new approximation may be modified so that the corresponding conditional information matrix can be made positive definite for every fixed η. In addition, a Bayesian procedure for contingency-table model checking is provided. An example of cross-classification between the educational level of a wife and fertility-planning status of couples is used for explanation. Various Laplacian approximations are computed and compared in this example and in an example of public school expenditures in the context of Bayesian analysis of the multiparameter Fisher-Behrens problem.     

CALGARY FAMILY INTERVENTION MODEL: ONE WAY TO THINK ABOUT CHANGE

This article defines and describes the Calgary Family Intervention Model (CFIM). CFIM is an organizing framework conceptualizing the intersect between a particular domain (i.e., cognitive, affective, or behavioral) of family functioning and a specific intervention offered by a health professional. Examples and discussion of interventions such as storying the illness experience, encouraging respite, and asking interventive questions are presented. CFIM is one way that health professionals can conceptualize about change.     

The Farm Crisis and Mental Health: A Longitudinal Study of the 1980s1

Abstract This paper examines rural/urban differences and trends in mental health during the farm crisis of the 1980s in a large panel sample from a midwestern state. A community research perspective, which attributes differences to life styles, culture, and community context, is contrasted with an economic stress perspective, which focuses on individual differences in economic circumstances as determinants of rural-urban differences in mental health. Survey samples from 1981, 1986, and 1989 are used to examine differences among seven categories of community type. Multiple regression analysis of the trend and panel data provide support for both the individual economic distress and community context models.     

State minimum wage laws: Youth coverage and impact

Federal minimum wage statutes cover only 70 percent of the work force and 30 percent of all employers. State laws are designed to close some of these coverage gaps and in some cases to set higher wage floors. Hence, differences in state wage floors and coverage should affect employment rates and wage distributions, particularly among low-skilled workers. Evidence from the National Longitudinal Ssurveys of Youth is mixed, however: State wage floors appear to have no impact on youth employment or entry wages, but coverage exemptions appear to increase both employment and wages. These observations underscore the need to include state provisions in models of minimum wage impacts, particularly for later periods (e.g., 1988–1991) when state wage floors were relatively higher.