MINING ERROR VARIANCE AND HITTING PAY-DIRT:

According to traditional error theory, sentiment measurements vary unsystematically from individual to individual. However, we find some patterned deviation in sentiments that characterize subsets of respondents within a seemingly homogeneous population. After demonstrating the existence of such patterns, we report an exploratory study aimed at identifying social characteristics of people with different patterns of sentiments. People embedded in multiple social networks have exaggerated sentiments that contour cultural patterns, and people with few social associations have attenuated sentiments conveying cultural detachment. In addition, people with disciplinary parents and romantic privation have some distinctive sentiments, depending on their gender.     

The Impact of Items and Anchors on Parent–Child Reports of Problem Behavior

Research has repeatedly demonstrated that parent and child reports of child behavior and emotional functioning often do not agree in terms of symptom severity or even symptom presence. Given the potential clinical impact that discrepant reports may have on the therapeutic process, a significant amount of research has addressed the factors influencing this observed discrepancy. Traditionally, this research has evaluated the impact of demographic factors on mean differences and obtained correlation coefficients between parent and child reports. The current research improves upon previous research in this area in two ways. First, the current research uses parent and child measures with identical rather than similar items as is commonly found in previous research. Second, the current research moves beyond identifying demographic influences on discrepant reports by explaining observed discrepancies in terms of differences in parent and child perceptions of typical child behavior.David Carlston and Benjamin Ogles are affiliated with Department of Psychology, Ohio University, Athens, USA.Funding for this project was provided by the Ohio Department of Mental Health.     

Inside the Sending State: The Politics of Mexican Emigration Control1

The social science of international migration has generally ignored labor emigration control policies. In the critical case of Mexico, however, the central government consistently tried to control the volume, duration, skills, and geographic origin of emigrants from 1900 to the early 1970s. A neopluralist approach to policy development and implementation shows that the failure of emigration control and the current abandonment of serious emigration restrictions are explained by a combination of external constraints, imposed by a highly asymmetrical interdependence with the United States, and internal constraints, imposed by actors within the balkanized Mexican state who recurrently undermined federal emigration policy through contradictory local practices.     

Determinants and Consequences of Social Trust*

This article provides an overview of social trust, examining its various aspects and components. Trust is best understood in a sociological sense by focusing on its important relational characteristic. Following this lead, the article discusses briefly how social trust relates to social capital and examines factors that shape the development of social trust, along with outcomes related to variations in trust, classifying them by analytical level (i.e., individual, community, group, organizational, and societal). The article concludes by assessing the strengths and weaknesses of existing research and by identifying some important questions that have not yet been adequately addressed.     

BAYESIAN SUBSET SELECTION AND MODEL AVERAGING USING A CENTRED AND DISPERSED PRIOR FOR THE ERROR VARIANCE

This article proposes a new data‐based prior distribution for the error variance in a Gaussian linear regression model, when the model is used for Bayesian variable selection and model averaging. For a given subset of variables in the model, this prior has a mode that is an unbiased estimator of the error variance but is suitably dispersed to make it uninformative relative to the marginal likelihood. The advantage of this empirical Bayes prior for the error variance is that it is centred and dispersed sensibly and avoids the arbitrary specification of hyperparameters. The performance of the new prior is compared to that of a prior proposed previously in the literature using several simulated examples and two loss functions. For each example our paper also reports results for the model that orthogonalizes the predictor variables before performing subset selection. A real example is also investigated. The empirical results suggest that for both the simulated and real data, the performance of the estimators based on the prior proposed in our article compares favourably with that of a prior used previously in the literature.