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.     

The Micro System of Deviance in Intimate Relationships*

Deviance in intimate relationships may lie as much within the micro system of such relationships as it does within the personalities of the actors involved. Using a Parsonsian framework, it is argued that the strain of systemically disequilibrated relationships can produce deviant personality adaptations which, in turn, intensify conflict and deviance in those relationships. It is also proposed that a reciprocal quality exists to such maladaptations, with each member of the dyad contributing to the amplification of a stable system of deviant behavior patterns within the relationship. Because the patterns of maladaptive dyads spill over into parent-child relationships, they have implications for understanding intergenerational transmission of deviance between intimates.     

MODEL-ASSISTED HIGHER-ORDER CALIBRATION OF ESTIMATORS OF VARIANCE

In survey sampling, interest often centres on inference for the population total using information about an auxiliary variable. The variance of the estimator used plays a key role in such inference. This study develops a new set of higher‐order constraints for the calibration of estimators of variance for various estimators of the population total. The proposed strategy requires an appropriate model for describing the relationship between the response and auxiliary variable, and the variance of the auxiliary variable. It is therefore referred to as a model‐assisted approach. Several new estimators of variance, including the higher‐order calibration estimators of the variance of the ratio and regression estimators suggested by Singh, Horn & Yu and Sitter & Wu are special cases of the proposed technique. The paper presents and discusses the results of an empirical study to compare the performance of the proposed estimators and existing counterparts.     

To Refer or Not to Refer: Exploring Family Therapists' Beliefs and Practices Related to the Referral of Lesbian,Gay, and Bisexual Clients

This study explored how negative beliefs toward lesbian, gay, and bisexual (LGB) individuals and LGB clinical competence influenced family therapists' beliefs and practices regarding referring based on the sexual orientation of the client. The sample consisted of 741 experienced clinicians. The results of this study indicated that the majority of the participants believe it is ethical to refer LGB clients; however, most had never made such a referral. Furthermore, participants who had referred based solely on the client's sexual orientation reported higher levels of negative beliefs toward LGB individuals and lower levels of LGB clinical competence. Finally, negative beliefs toward LGB persons not only predicted the practice of referring, but also the belief that it is ethical to refer an LGB client.     

Process evaluation of an environmental walking and healthy eating pilot in small rural worksites

Small Steps are Easier Together (SS) was a pilot environmental intervention in small rural worksites in Upstate New York in collaboration with Extension educators. Worksite leaders teamed with co-workers to select and implement environmental changes to increase walking steps over individual baseline and to choose healthy eating options over 10 weeks. Participants were 226 primarily white, women employees in 5 sites. A mixed methods process evaluation, conducted to identify determinants of intervention effectiveness and to explain differences in outcomes across worksites, included surveys, self-reports of walking and eating, interviews, focus groups, and an intervention log. The evaluation assessed reach, characteristics of recruited participants, dose delivered, dose received, and context and compared sites on walking and eating outcomes. Emergent elements of participant-reported dose received included: active leadership, visible environmental changes, critical mass of participants, public display of accomplishments, accountability to co-workers, and group decision making. Participants at sites with high reach and dose were significantly more likely than sites with low reach and dose to achieve intervention goals. Although this small pilot needs replication, these findings describe how these evaluation methods can be applied and analyzed in an environmental intervention and provide information on trends in the data.     

Gender and racial/ethnic differences in predicting adolescent sexual risk: athletic participation versus exercise

Though often conflated, informal physical exercise and organized athletic participation have very different implications for adolescent sexual risk outcomes. The purpose of this research is to disaggregate strenuous exercise from sports, examine how each is associated with sexual risk, and explain the observed differences using the conceptual lens of cultural resource theory. Using a nationally representative sample of over 16,000 public and private high school students, we employ logistic regression to test hypotheses about the gender-specific and race-specific effects of strenuous exercise and athletic participation on adolescent sexual risk behavior. The results show that both forms of physical activity buffer sexual risk for girls. Strenuous exercise is associated with increased odds of sexual risk for boys. Sports and race interact to influence boys' sexual risk outcomes: Athletic participation is associated with lowered odds of sexual risk for white male adolescents, but heightened odds of sexual risk for black male adolescents.     

Empirical Bayes Small-Area Estimation Using Logistic Regression Models and Summary Statistics

Many of the available methods for estimating small-area parameters are model-based approaches in which auxiliary variables are used to predict the variable of interest. For models that are nonlinear, prediction is not straightforward. MacGibbon and Tomberlin and Farrell, MacGibbon, and Tomberlin have proposed approaches that require microdata for all individuals in a small area. In this article, we develop a method, based on a second-order Taylor-series expansion to obtain model-based predictions, that requires only local-area summary statistics for both continuous and categorical auxiliary variables. The methodology is evaluated using data based on a U.S. Census.     

Estimation in an empirical bayes model for longitudinal and cross‐sectionally clustered binary data

Some studies generate data that can be grouped into clusters in more than one way. Consider for instance a smoking prevention study in which responses on smoking status are collected over several years in a cohort of students from a number of different schools. This yields longitudinal data, also cross‐sectionaliy clustered in schools. The authors present a model for analyzing binary data of this type, combining generalized estimating equations and estimation of random effects to address the longitudinal and cross‐sectional dependence, respectively. The estimation procedure for this model is discussed, as are the results of a simulation study used to investigate the properties of its estimates. An illustration using data from a smoking prevention trial is given.