When Working Hard Is Not Enough for Female and Racial/Ethnic Minority Apprentices in the Highway Trades

Drawing on employment records, qualitative interviews, and a survey, we explore the experiences of apprentices in the highway trades in Oregon. We demonstrate that female and racial/ethnic minority apprentices have lower rates of recruitment and retention and disproportionately face challenges with interpersonal interactions, hiring practices, and supervisory practices. Yet, we find a pervasive narrative that attributes apprentices' success to “hard work,” which contributes to the legitimacy of these inequalities. Consistent with the conceptualization of work organizations as inequality regimes, we argue that the apprenticeship system has policies, practices, and ideologies that are on the surface gender and race/ethnicity neutral, yet lead to the perpetuation of inequalities.     

Sources of family violence

This paper suggests a direction for the exploration of the causes of family violence. Explanatory models of family violence were considered in this regard, with the recommendation that a multi-determined model should be considered to ensure the most accurate explanation. We suggest that family violence will be best understood and prevented or alleviated, if a model is used that considers the interaction of structural violence and the personality features of all the family members.     

Monte Carlo methods for nonparametric survival model determination

In the causal analysis of survival data a time-based response is related to a set of explanatory variables. Definition of the relation between the time and the covariates may become a difficult task, particularly in the preliminary stage, when the information is limited. Through a nonparametric approach, we propose to estimate the survival function allowing to evaluate the relative importance of each potential explanatory variable, in a simple and explanatory fashion. To achieve this aim, each of the explanatory variables is used to partition the observed survival times. The observations are assumed to be partially exchangeable according to such partition. We then consider, conditionally on each partition, a hierarchical nonparametric Bayesian model on the hazard functions. We define and compare different prior distribution for the hazard functions.     

Government Debt and Excess Sensitivity of Private Consumption: Estimates from OECD Countries

This article investigates the role of government debt in the degree of excess sensitivity of private consumption to current disposable income. Because this type of excess sensitivity is generally attributed to liquidity constraints, this amounts to a test of the impact of government debt on the amount of credit extended to individuals. Controlling for financial liberalization we find that, for a panel of OECD countries in the 1990s, a high government debt leads to more excess sensitivity. This result supports the idea that a high government debt induces lenders to tighten credit conditions. Our findings survive several robustness checks.     

A STRUCTURAL AND DEVELOPMENTAL ANALYSIS OF SYMPTOMATIC ADOPTED CHILDREN AND THEIR FAMILIES*

Based on a mental health pilot project with 34 adoptive families, this paper examines the unique differences of adoptive families from other family systems. The paper defines the context of the adopted child's symptoms and the families' characteristics. The relationship between adoption and the family's structure and development are analyzed.     

Unemployment Duration in an Unemployment Blackspot

This paper analyses the factors affecting the duration of an unemployment spell amongst a sample of exclusively long-term unemployed individuals. The results indicate that person-specific unemployment propensities have a significant effect on re-employment probabilities. These effects, however, vary significantly by gender and religion. The results also indicate statistically significant negative ‘duration dependence’ effects. The evidence suggests that employers regard long unemployment durations as a ‘negative signal’ about an applicant's potential productivity. The latter implies that, in terms of government policies aimed at reducing unemployment, the demand-side of the unemployment equation should be given greater emphasis.     

The Gender of Pregnancy: Masculine Lesbians Talk about Reproduction

Heterosexism and patriarchy collude to create an expectation of pregnancy for all women. In addition, the bodily production of pregnancy has been socially gendered as feminine because of its association with female-bodied people. These two ideological codes—that all women should become mothers through pregnancy and that pregnancy is a femininely gendered endeavor—suggest conundrums for masculine lesbians. This study relies on interview data with 14 childfree masculine-identified lesbians about the ways in which they are able (or unable) to imagine themselves as pregnant people in their future lives. Participants’ navigation of the concept of pregnancy reveal the complexity of gendered bodies and gender practice.     

The spiritual nature of service-learning

Service-learning, by its very nature, fosters young people's spiritual development, especially in experiencing a sense of interconnectedness with others and the rest of the world; opening one's heart; and expanding self-inquiry and self-knowledge.     

Bayesian factor analysis for spatially correlated data: application to cancer incidence data in Scotland

A hierarchical Bayesian factor model for multivariate spatially correlated data is proposed. Multiple cancer incidence data in Scotland are jointly analyzed, looking for common components, able to detect etiological factors of diseases hidden behind the data. The proposed method searches factor scores incorporating a dependence within observations due to a geographical structure. The great flexibility of the Bayesian approach allows the inclusion of prior opinions about adjacent regions having highly correlated observable and latent variables. The proposed model is an extension of a model proposed by Rowe (2003a) and starts from the introduction of separable covariance matrix for the observations. A Gibbs sampling algorithm is implemented to sample from the posterior distributions.