Frontiers in Social Science features new research in the flagship journals of the Social Science Research Council’s founding disciplinary associations. Every month we publish a new selection of articles from the most recent issues of these journals, marking the rapid advance of the frontiers of social and behavioral science.
A statistical model is developed to analyze how severe thunderstorm indicators vary across space and time in the U.S., especially under the influence of seasonal changes and El Niño events.
Severe thunderstorms cause substantial economic and human losses in the United States. Simultaneous high values of convective available potential energy (CAPE) and storm relative helicity (SRH) are favorable to severe weather, and both they and the composite variable PROD=√CAPE×SRH can be used as indicators of severe thunderstorm activity. Their extremal spatial dependence exhibits temporal non-stationarity due to seasonality and large-scale atmospheric signals such as El Niño-Southern Oscillation (ENSO). In order to investigate this, we introduce a space-time model based on a max-stable, Brown–Resnick, field whose range depends on ENSO and on time through a tensor product spline. We also propose a max-stability test based on empirical likelihood and the bootstrap. The marginal and dependence parameters must be estimated separately owing to the complexity of the model, and we develop a bootstrap-based model selection criterion that accounts for the marginal uncertainty when choosing the dependence model. In the case study, the out-sample performance of our model is good. We find that extremes of PROD, CAPE, and SRH are generally more localized in summer and, in some regions, less localized during El Niño and La Niña events, and give meteorological interpretations of these phenomena. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
In Senegal, women with Type II diabetes combat social stigma from weight loss that negatively affects their physical health and community participation.
In Senegal, Type II diabetes often causes rapid weight loss. Weight loss is usually the reason women will finally seek out a biomedical diagnosis for their ailment. Loss of weight has many negative connotations for Senegalese women—HIV/AIDS, tuberculosis, financial troubles, or an unhappy marriage. When women lose weight, they become the subject of rumors and gossip in their communities. This leads to isolation. Research has shown that isolation has deleterious mental health effects, especially in places as communal as Senegal. Worsening mental health can also exacerbate diabetes. This article explores Senegalese women's experiences with weight loss due to Type II diabetes and the effects their weight loss, in addition to their diabetes, has on their lived experience and their social networks.