The American sociologist: Characteristics in the 1990s

This article describes the characteristics, theoretical preferences, and political orientations of sociologists in the United States. The findings are the most representative of their kind reported to date. Other professional groups, such as psychiatrists, have been studied over time (Gallagher, 1977; Gallagher et al., 1987; Gallagher et al., 1990), but studies of sociologists have been almost non-existent. In fact, there has only been one study of this nature conducted in the 1990s, and that one sampled only sociologists whose names appeared on the membership list of the American Sociological Association (Sanderson and Ellis, 1992). However, that sampling frame did not provide a representative cross-section of American sociologists because it excluded the large proportion of sociologists who are not members of the ASA and who probably are systematically different than members. It is ironic that sociologists who intensively study the characteristics of all sorts of groups know so little about themselves. That is a major reason why this project was undertaken.     

Does the number of sex partners affect educational attainment? Evidence from female respondents to the Add Health

We use data on young women from the National Longitudinal Study of Adolescent Health to explore the relationship between number of sex partners and educational attainment. Using the average physical development of male schoolmates to generate plausibly exogenous variation in number of sex partners, instrumental variables estimates suggest that number of sex partners is negatively related to educational attainment. This result is consistent with the argument that romantic involvements are time consuming and can impose substantial emotional costs on young women.     

Interorganizational Determinants of Environmental Purchasing: Initial Evidence from the Consumer Products Industries*

Environmental purchasing consists of the purchasing function's involvement in activities that include reduction, recycling, reuse, and substitution of materials. Despite the potentially important role that the purchasing function can play in a firm's environmental activities, little research has been performed to date that examines the factors that impact environmental purchasing. The authors develop and empirically test a theoretical model that examines how interorganizational factors both drive and constrain purchasing's involvement in environmental activities. The empirical findings suggest that environmental purchasing activities will be facilitated through increased coordination with suppliers as well as downstream members of the supply chain, including retailers. The results also suggest the need for increased coordination within the firm, particularly between the purchasing function on the inbound side and marketing and distribution functions on the outbound side.     

The unique relationship between childhood sexual abuse,self-injury and suicide ideation: The mediating role of emotion dysregulation

Child sexual abuse (CSA) has serious short-term and long-term effects, including non-suicidal self-injury (NSSI) and suicidal ideation (SI). One possible thread linking CSA to NSSI and suicide risk is emotion dysregulation. The current study assessed whether facets of emotion dysregulation mediated relations of NSSI behaviours and functions, and SI. Participants (N = 121; Mean age = 18.69, age-range 18–22; 78 per cent female), college students with a history of childhood trauma, completed an online survey. Results indicated that facets of emotion dysregulation (i.e. clarity, non-acceptance) mediated the relationship between CSA and SI. CSA was associated with automatic negative reinforcement, social negative and social positive reinforcement NSSI functions, but was not associated with NSSI behaviours. Emotion dysregulation facets did not mediate the relationship between CSA and NSSI functions. Findings highlight the need to help CSA survivors have clarity and acceptance of emotional experiences to reduce SI risk. This research did not receive any specific grant from funding agencies in the public, commercial or not-for-profit sectors.     

Sibship and Inequality Beliefs: Do Siblings Have a Liberalizing or Conservatizing Effect?

How do individuals come to hold certain beliefs about meritocracy, individualism, and redistribution? Several sociodemographic factors are regularly used to understand variation in these beliefs, but other predictors remain untested. Meanwhile, scholars studying family dynamics are increasingly turning their attention toward the long-term social effects of distinct family features. One facet of this work focuses on the social role of siblings. We investigate the relationship at the intersection of these literatures. How does growing up with (more) siblings influence one's inequality beliefs? Do siblings promote collectivism or might these same relationships foster competition and individualism? Could trust be the mechanism connecting sibship size with inequality beliefs? Or, do sibling effects reflect a broader promotion of conservative thinking in larger families? We investigate these questions using data from the General Social Survey from 1984 to 2018. Our results indicate that siblings are associated with more conservative meritocracy beliefs. On the other hand, we find limited evidence of siblings influencing attitudes toward redistribution.     

Bayesian local influence for survival models

The aim of this paper is to develop a Bayesian local influence method (Zhu et al. 2009, submitted) for assessing minor perturbations to the prior, the sampling distribution, and individual observations in survival analysis. We introduce a perturbation model to characterize simultaneous (or individual) perturbations to the data, the prior distribution, and the sampling distribution. We construct a Bayesian perturbation manifold to the perturbation model and calculate its associated geometric quantities including the metric tensor to characterize the intrinsic structure of the perturbation model (or perturbation scheme). We develop local influence measures based on several objective functions to quantify the degree of various perturbations to statistical models. We carry out several simulation studies and analyze two real data sets to illustrate our Bayesian local influence method in detecting influential observations, and for characterizing the sensitivity to the prior distribution and hazard function.     

Why a Bayesian approach to safety analysis in pharmacovigilance is important

Large databases of routinely collected data are a valuable source of information for detecting potential associations between drugs and adverse events (AE). A pharmacovigilance system starts with a scan of these databases for potential signals of drug-AE associations that will subsequently be examined by experts to aid in regulatory decision-making. The signal generation process faces some key challenges: (1) an enormous volume of drug-AE combinations need to be tested (i.e. the problem of multiple testing); (2) the results are not in a format that allows the incorporation of accumulated experience and knowledge for future signal generation; and (3) the signal generation process ignores information captured from other processes in the pharmacovigilance system and does not allow feedback. Bayesian methods have been developed for signal generation in pharmacovigilance, although the full potential of these methods has not been realised. For instance, Bayesian hierarchical models will allow the incorporation of established medical and epidemiological knowledge into the priors for each drug-AE combination. Moreover, the outputs from this analysis can be incorporated into decision-making tools to help in signal validation and posterior actions to be taken by the regulators and companies. We discuss in this paper the apparent advantage of the Bayesian methods used in safety signal generation and the similarities and differences between the two widely used Bayesian methods. We will also propose the use of Bayesian hierarchical models to address the three key challenges and discuss the reasons why Bayesian methodology still have not been fully utilised in pharmacovigilance activities.