A gender-based incidence study of workplace violence in psychiatric and forensic settings

Limited data exist analyzing the role of gender in workplace violence in health care settings. This study examined whether different types of threatening incidents with patients (physical, verbal, sexual, or posturing) were salient to male versus female staff across psychiatric settings (inpatient forensic, inpatient acute/chronic psychiatric, and outpatient psychiatric). Results indicated that although women disproportionately experienced sexualized threats, they were not more likely to report such incidents as salient and threatening. The study also assessed the extent to which situational variables contributed to staff's feelings of threat. Results showed that rapport with the patient, quality of relationships with coworkers, and presence of coworkers in the area were not significantly related to how threatened staff felt in a recent threatening incident. Findings are discussed within the context of staff training and organizational benefits.     

Racial Differences in Networks: Do Neighborhood Conditions Matter?*

Objectives. This study examines which of five neighborhood conditions help account for racial differences in social networks. Methods. The data set is the Urban Poverty and Family Life Survey, a survey of blacks, whites, Mexicans, and Puerto Ricans clustered in Chicago Census tracts, matched to 1990 Census data. I estimate HGLM models predicting five indicators of social isolation and five indicators of number of social ties as a function of race, controls, and the following neighborhood conditions: neighborhood poverty, proportion black, residential stability, ethnic heterogeneity, and population density. Results. Although initial estimates confirm the existence of racial differences in network size, most of these differences are not robust to controls for neighborhood conditions. Among the neighborhood variables, only neighborhood poverty is consistently associated with size of social networks. Conclusions. Findings suggest that while residential segregation has created conditions in which some races are more likely to live in high‐poverty neighborhoods, it is the poverty, not the racial composition, of the neighborhoods that is significantly associated with weaker social ties.     

The Psycho-Ecology of Armed Conflict

As natural resources are depleted and global population grows, environmental security is becoming an increasingly salient dimension of long-term peace. In this article, we discuss current views of environmental security and go on to argue that the social psychological dimensions of resource-based conflict should also be addressed. We briefly describe six examples of such conflicts, and conclude that psychologists can play an important role in promoting peace, by bringing attention to, and helping find ways to mitigate, the psycho-ecological dimensions of armed conflict.     

Mixed Consequences of Government Aid for New Venture Creation: Evidence from Italy

Most countries have designed programsto stimulate the birth and development of new firms.One of the most important issues in evaluating theimpact of public entrepreneurial policies is toanalyze their influence on the post-entry performanceof the new ventures. This paper examines how the mostimportant government program to encourageentrepreneurship in Italy (the Law 44 program) affectsseveral aspects of the early performance of new firms.A sample of new firms receiving government aid iscompared to a matched sample of new firms notreceiving public assistance, i.e., ``control' firms. The control firms were born in the same year, launchedtheir business in the same geographical area andoperate in the same industry classification. Resultsshow that the public program produces mixed effects.Government aid allows firms to have a higher level oftechnology. However, government funding gives rise toentrepreneurial start-ups, which are not fullyefficient. A discussion of these findings andsuggestions for future research are presented.     

Does Financial Inclusion Diminish Poverty and Inequality? A Panel Data Analysis for Latin American Countries

Despite great developmental efforts in recent decades, Latin America still presents high levels of poverty and inequality when compared to developed nations. As explored widely in the literature, one potential instrument to diminish these issues is financial inclusion, including the access and usage of financial services by all people. Specifically, this paper verifies if financial inclusion and technology adoption decrease the poverty headcount ratio and the Gini index (i.e., inequality) of 13 Latin America countries (Argentina, Bolivia, Brazil, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Honduras, Panama, Paraguay, Peru, and Uruguay). To perform such analysis, an unbalanced panel dataset was built, and the Feasible Generalized Least Squares (FGLS) and the Limited Information Maximum Likelihood (LIML) techniques were employed. The results suggest that, in accordance with previous studies, financial inclusion is a powerful tool to tackle poverty and inequality. Additionally, the combined effects of financial inclusions and technology (i.e., mobile use) are also capable of decreasing the poverty and inequality levels. We discuss the policy implications of our findings and suggest a future research agenda.

     

Effects of air pollution and weather on the initial COVID-19 outbreaks in United States,Italy, Spain,and China: A comparative study

Contrasting effects have been identified in association of weather (temperature and humidity) and pollutant gases with COVID-19 infection, which could be derived from the influence of lockdowns and season change. The influence of pollutant gases and climate during the initial phases of the pandemic, before the closures and the change of season in the northern hemisphere, is unknown. Here, we used a spatial-temporal Bayesian zero-inflated-Poisson model to test for short-term associations of weather and pollutant gases with the relative risk of COVID-19 disease in China (first outbreak) and the countries with more cases during the initial pandemic (the United States, Spain and Italy), considering also the effects of season and lockdown. We found contrasting association between pollutant gases and COVID-19 risk in the United States, Italy, and Spain, while in China it was negatively associated (except for SO₂). COVID-19 risk was positively associated with specific humidity in all countries, while temperature presented a negative effect. Our findings showed that short-term associations of air pollutants with COVID-19 infection vary strongly between countries, while generalized effects of temperature (negative) and humidity (positive) with COVID-19 was found. Our results show novel information about the influence of pollution and weather on the initial outbreaks, which contribute to unravel the mechanisms during the beginning of the pandemic.     

Is Arbitration Habit Forming? The Narcotic Effect of Arbitration Use

This paper explores the existence of structural state dependence in arbitration use where it is legally mandated to resolve labor–management bargaining disputes. Previous studies have found both positive state dependence (the narcotic effect) and negative state dependence. This paper reports a negative state dependence for the Minnesota public sector during the period 1973 to 1980. A weak positive trend in arbitration probabilities and a positive relationship between current arbitration probabilities and the proportion of bargainers engaging in arbitration during the same calendar year are also found. An analysis of the dynamic implications of these findings does not support fears that compulsory arbitration schemes are unstable or lead to arbitration as the dominant settlement mode.     

Multimode time-cost-robustness trade-off project scheduling problem under uncertainty

The time/cost trade-off problem is a well-known project scheduling problem that has been extensively studied. In recent years, many researchers have begun to focus on project scheduling problems under uncertainty to cope with uncertain factors, such as resource idleness, high inventory, and missing deadlines. To reduce the disturbance from uncertain factors, the aim of robust scheduling is to generate schedules with time buffers or resource buffers, which are capped by project makespan and project cost. This paper addresses a time-cost-robustness trade-off project scheduling problem with multiple activity execution modes under uncertainty. A multiobjective optimization model with three objectives (makespan minimization, cost minimization, and robustness maximization) is constructed and three propositions are proposed. An epsilon-constraint method-based genetic algorithm along with three improvement measures is designed to solve this NP-hard problem and to develop Pareto schedule sets, and a large-scale computational experiment on a randomly generated dataset is performed to validate the effectiveness of the proposed algorithm and the improvement measures. The final sensitivity analysis of three key parameters shows their distinctive influences on the three objectives, according to which several suggestions are given to project managers on the effective measures to improve the three objectives.