Migration, emotions and policies of sensibilities in Central America

In Central America, irregular migration to the United States has become an alternative with the aim of finding better living conditions, safety or to achieve the ‘American Dream’. Mobility is linked to conflict networks associated with poverty and violence. This article aims to analyze the problem of migration in Central America and the policies of sensibilities associated with it. First, an overview of social studies on emotions in the region is presented. Then, an analysis of migration policies and the main programs implemented to control irregular migration from Central America to North America, is introduced, specifically the Agreement that designates Guatemala as a ‘Safe Third Country’. As well, a characterization of the migratory context, its institutionality and the mechanisms for containing massive migratory flows is presented, as a demonstration of the relationship between state actions, sensibilities and social support mechanisms associated with migration and migrants’ feelings.

The impact of anodal tDCS on attentional networks as a function of trait anxiety and depressive symptoms: A preregistered double-blind sham-controlled experiment

Attention is a multifaceted construct, including three distinct attentional networks: the alerting, orienting, and executive conflict networks. Recently, researchers have started to envision strategies to enhance the attentional networks, and transcranial Direct Current Stimulation (tDCS) has emerged as a promising tool to do so, especially regarding the executive conflict network. On the other hand, other research lines have suggested that anodal tDCS might yield more substantial impacts among depressive and anxious participants. In this preregistered study, we thus examined two questions. First, we wanted to replicate previous observations and tested whether anodal tDCS does improve the executive conflict network's efficiency. Second, we set out to clarify the impact of anxiety and depressive symptoms on this effect. To do so, we adopted a double-blind within-subject protocol in an unselected sample (n = 50) and delivered a single session of anodal— applied over the dorsolateral part of the left prefrontal cortex—versus sham tDCS during the completion of a task assessing the attentional networks. We assessed anxiety and depressive symptoms at baseline. Although there were no significant direct effects of tDCS on the attentional networks, we found that the higher the levels of depression and trait anxiety, the larger the executive conflict network's enhancement during tDCS. By highlighting the importance of trait anxiety and depression when considering the impact of tDCS on the attentional networks, this study fulfills a valuable niche in clinical neuroscience, wherein preclinical data provide critical clues for larger, more definitive future translational efforts.

Predicting the severity of civil wars: An actor-centric approach

We introduce an actor-centric approach to predict the severity of conflict one and six months into the future. We argue that the prediction of conflict severity needs to focus on the actors that are responsible for conducting armed violence. Hence, we predict the severity of conflict in government-rebel organization dyads. Our predictors focus especially on rebel organization characteristics, behavior, and the conflict networks actors are embedded in. Our statistical learning approach relies on random forests to predict the severity of conflict. We demonstrate that our model performs especially well distinguishing high levels of severity from very low levels.

Escalation of competition into conflict in competitive networks of Formula One drivers

This article investigates the factors that escalate competition into dangerous conflict. Recent sociological theorizing claims that such escalations are particularly likely in dyads of structurally equivalent people (i.e., actors who have the same relations with the same third parties). Using panel data on Formula One races from 1970 through 2014, we model the probability that two drivers collide on the racetrack (an observable trace of conflict) as a function of their structural equivalence in a dynamic network of competitive relationships. Our main hypothesis, that the likelihood of conflict rises with structural equivalence, receives empirical support. Our findings also show that the positive association between structural equivalence and conflict is neither merely a matter of contention for official position nor an artifact of inherently hostile parties spatially exposed to each other. Our analyses further reveal that this positive association is concentrated in a number of theoretically predictable conditions: among age-similar dyads, among stronger performers, in stable competitive networks, and in safe, rather than dangerous, weather conditions. Implications for future research on conflict, networks, and tournaments are discussed.