Stigma toward internalizing and externalizing disorders: How do adolescents perceive their peers? A network analysis approach

This study's first aim was to explore whether stigma's facets differ between internalizing and externalizing disorders in adolescence. The second aim was to compare the relationships among stigma's facets toward these disorders. Two vignettes depicting a peer with Major Depressive Disorder (MDD) or Attention-Deficit Hyperactivity Disorder (ADHD) were used with 616 adolescents in Italy. A Repeated measure MANOVA showed biogenetic causes, social distancing, and discomfort were more attributed to depression, while dangerousness to ADHD. Furthermore, a Psychometric Network Analysis showed no differences between these disorders in the relations among stigma's components. However, dangerousness seemed to be among the nodes with the highest levels of “strength,” confirming previous literature that shows that dangerousness plays a major role in stigma.     

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.     

Transnational social protection infrastructures: African migrants in Mexico

In the past years, increasingly restrictive migration policies have pushed many migrants to seek new and more risky migration routes. Many studies have investigated aspects of social protection for migrants from the Global South in industrialized countries of the Global North, with powerful welfare states. Yet, such focus has failed to understand the complexities during the migration process, where people often spend uncertain periods of time in transit countries and the state is frequently absent. In these contexts, social protection is predominantly provided by the third sector (TS) and informal networks both nationally and transnationally. Based on ethnographic fieldwork conducted with African migrants and TS organizations in Mexico, this paper explores the different and often semi-formal relationships between the TS, the state, and the migrants that result in complex transnational social protection infrastructures to cover the migrants' basic social protection needs.     

On the Failure of the Bootstrap for Matching Estimators

Matching estimators are widely used in empirical economics for the evaluation of programs or treatments. Researchers using matching methods often apply the bootstrap to calculate the standard errors. However, no formal justification has been provided for the use of the bootstrap in this setting. In this article, we show that the standard bootstrap is, in general, not valid for matching estimators, even in the simple case with a single continuous covariate where the estimator is root‐N consistent and asymptotically normally distributed with zero asymptotic bias. Valid inferential methods in this setting are the analytic asymptotic variance estimator of Abadie and Imbens (2006a) as well as certain modifications of the standard bootstrap, like the subsampling methods in Politis and Romano (1994).