Shortcomings and/or Missed Opportunities of the Global Compacts for the Protection of Forced Migrants

The Global Compact for Safe, Orderly and Regular Migration (GCM) and the Global Compact on Refugees (GCR) are norm‐creating exercises, in the sense of being international legal documents for a new framework that reinforces existing structures and attempt to renew migration governance globally. They were expected to further develop the protection of all migrants. However, despite some progress, there are shortcomings and/or missed opportunities in what they were able to achieve, especially in the case of the protection of forced migrants. Understanding these shortcomings and/or missed opportunities as being conceptual and institutional in nature, and to assess both these sets, this article presents the idea of forced migration and the lack of international protection of forced migrants (part 1), describes the protection of forced migrants achieved by the Compacts (part 2), and ends by assessing the shortcomings and/or missed opportunities in both Compacts (part 3).     

Pathways from physical childhood abuse to partner violence in young adulthood

Analyses investigated several competing hypotheses about developmental pathways from childhood physical abuse and early aggression to intimate partner violence (IPV) for young adult males and females at age 24. Potential intervening variables included: adolescent violence (age 15 to 18), negative emotionality at age 21, and quality of one's relationship with an intimate partner at age 24. At the bivariate level, nearly all variables were associated in the expected directions. However, tests of possible intervening variables revealed only a few significant results. For males, a strong direct effect of abuse on later partner violence was maintained in each model. For females, the quality of one's relationship with an intimate partner did appear to mediate the effect of childhood abuse on later violence to a partner, raising the possibility of gender differences in developmental pathways linking abuse to IPV. Implications with regard to prevention are discussed.     

Athletic involvement and its relevance to hazardous alcohol use and drinking game participation in female college athletes: a preliminary investigation

OBJECTIVE AND PARTICIPANTS: The authors designed this cross-sectional study to examine sports team differences in hazardous alcohol use and drinking game participation, as well as the social correlates of these behaviors among female college athletes (N = 176; M age = 19.9 years, SD = 1.24, range = 18-22). METHODS: Respondents completed self-report surveys in small groups. They reported drinking behaviors, frequency of team social events involving alcohol use, and team cohesion. RESULTS: The authors found significant differences across sports teams with regard to hazardous alcohol use and participation in drinking games with teammates. Findings also revealed that a high frequency of team social events involving alcohol use was associated with elevated use and an increased likelihood of drinking game participation. CONCLUSIONS: The authors discuss future research directions and implications.     

Subjective machines: Probabilistic risk assessment based on deep learning of soft information

For several years machine learning methods have been proposed for risk classification. While machine learning methods have also been used for failure diagnosis and condition monitoring, to the best of our knowledge, these methods have not been used for probabilistic risk assessment. Probabilistic risk assessment is a subjective process. The problem of how well machine learning methods can emulate expert judgments is challenging. Expert judgments are based on mental shortcuts, heuristics, which are susceptible to biases. This paper presents a process for developing natural language-based probabilistic risk assessment models, applying deep learning algorithms to emulate experts’ quantified risk estimates. This allows the risk analyst to obtain an a priori risk assessment when there is limited information in the form of text and numeric data. Universal sentence embedding (USE) with gradient boosting regression (GBR) trees trained over limited structured data presented the most promising results. When we apply these models’ outputs to generate survival distributions for autonomous systems’ likelihood of loss with distance, we observe that for open water and ice shelf operating environments, the differences between the survival distributions generated by the machine learning algorithm and those generated by the experts are not statistically significant.     

Topiramate Combined with Cognitive Restructuring for the Treatment of Gambling Disorder: A Two-Center,Randomized, Double-Blind Clinical Trial

Gambling disorder (GD) is a prevalent condition for which no pharmacological treatment has yet been approved, although there is evidence that topiramate can reduce impulsivity in GD and craving in various addictive behaviors. The goal of this study was to investigate the effectiveness of topiramate combined with cognitive restructuring for GD in a two-center, randomized, double-blind clinical trial. Participants were individuals seeking outpatient treatment for GD (n = 30), treated with either topiramate or placebo combined with a brief cognitive intervention, over a 12-week period, the dose of topiramate being tapered up during the first 8 weeks. The main outcome measures were gambling craving, behavior, and cognitive distortions; impulsivity; depression and social adjustment. Topiramate proved superior to placebo in reducing gambling craving (P = 0.017); time and money spent gambling (P = 0.007 and P = 0.047, respectively); cognitive distortions related to gambling (P = 0.003); and social adjustment (P = 0.040). We found no significant effects on impulsivity or depression. These findings are in contrast with data from a previous clinical trial with topiramate for GD. In the current study, we found that topiramate affects features specifically related to gambling addiction and had no significant effect on associated phenomena such as impulsiveness and depression. We believe that this response could be due to synergistic interaction between topiramate and the cognitive intervention.     

Thinking about gender, thinking about a common space of observation and discussion of the work activity of the other: the case of bus drivers

The work activity of urban bus drivers is held in the public space and characterized by a constant vigilance, but the moments of observation the colleagues' work are scarce. This fact results in a paradox--it is a work activity that is more visible to "outsiders" than to "insiders"--which has an important impact on the debate of the work activity from a perspective of gender and the women's work in a predominantly male context. Ergonomic analysis of work and semi-structured interviews were conducted with 32 urban public transport drivers, 16 women and 16 men. The results reveal the lack of conditions for the drivers' knowledge of the activity of another, especially when that other is a woman--while men attribute characteristics to women based on gender stereotypes and an extension of their role in the private sphere, women relate them with the need to prove their competence and be recognized. It is proposed the development, in the context of training, of a space for debate and knowledge of the activity of the other and for the creation of conditions for another integration of women in the profession and for another visibility of their work.     

Learning from international business affiliates: developing resource-based learning capacity through networks and knowledge acquisition

Resource-based learning capacity (RBLC) is an organization's specific resources – both human and tangible – that can be organized to enhance learning processes. This study develops and tests a model that examines the relationship between the learning efforts of focal firms from their international business affiliates (IBAs) – organizations located outside the focal firm's domestic market with whom the focal firm has a relationship – and the focal firms' RBLC. This learning process refers to the transfer of knowledge from the IBA to the focal firm. Results indicate that while learning effectiveness positively influences the RBLC of the focal firm, learning efficiency has a negative impact on RBLC. The IBA's home country network centrality and the tie strength between the focal organization and the IBA are found to influence learning effectiveness positively. Tie strength also enhances learning efficiency. Finally, the findings indicate that the IBA's home country network centrality enhances the strength of the ties between the focal organization and its IBA.     

Bivariate beta regression models: joint modeling of the mean,dispersion and association parameters

In this paper a bivariate beta regression model with joint modeling of the mean and dispersion parameters is proposed, defining the bivariate beta distribution from Farlie–Gumbel–Morgenstern (FGM) copulas. This model, that can be generalized using other copulas, is a good alternative to analyze non-independent pairs of proportions and can be fitted applying standard Markov chain Monte Carlo methods. Results of two applications of the proposed model in the analysis of structural and real data set are included.