Suchergebnisse

How well do governments represent the societies they serve? A key aspect of this question concerns the extent to which leaders reflect the demographic features of the population they represent. To address this important issue in a systematic manner, we propose a unified approach for measuring descriptive representation. We apply this approach to newly collected data describing the ethnic, linguistic, religious, and gender identities of over fifty thousand leaders serving in 1,552 political bodies across 156 countries. Strikingly, no country represents social groups in rough proportion to their share of the population. To explain this shortfall, we focus on compositional factors—the size of political bodies as well as the number and relative size of social groups. We investigate these factors using a simple model based on random sampling and the original data described above. Our analyses demonstrate that roughly half of the variability in descriptive representation is attributable to compositional factors.

AbstractSome scholars build models to classify documents into chosen categories. Others, especially social scientists who tend to focus on population characteristics, instead usually estimate the proportion of documents in each category—using either parametric "classify-and-count" methods or "direct" nonparametric estimation of proportions without individual classification. Unfortunately, classify-and-count methods can be highly model-dependent or generate more bias in the proportions even as the percent of documents correctly classified increases. Direct estimation avoids these problems, but can suffer when the meaning of language changes between training and test sets or is too similar across categories. We develop an improved direct estimation approach without these issues by including and optimizing continuous text features, along with a form of matching adapted from the causal inference literature. Our approach substantially improves performance in a diverse collection of 73 datasets. We also offer easy-to-use software that implements all ideas discussed herein.

The British Heart Foundation and the European Union large-scale collaborative project METOXIA funded this research.

Abstract. Background: Infectious disease-related public health emergencies (epidemics) may increase suicide risk, and high-quality evidence is needed to guide an international response. Aims: We investigated the potential impacts of epidemics on suicide-related outcomes. Method: We searched MEDLINE, EMBASE, PsycInfo, CINAHL, Scopus, Web of Science, PsyArXiv, medRxiv, and bioRxiv from inception to May 13–16, 2020. Inclusion criteria: primary studies, reviews, and meta-analyses; reporting the impact of epidemics; with a primary outcome of suicide, suicidal behavior, suicidal ideation, and/or self-harm. Exclusion criteria: not concerned with suicide-related outcomes; not suitable for data extraction. PROSPERO registration: #CRD42020187013. Results: Eight primary papers were included, examining the effects of five epidemics on suicide-related outcomes. There was evidence of increased suicide rates among older adults during SARS and in the year following the epidemic (possibly motivated by social disconnectedness, fears of virus infection, and concern about burdening others) and associations between SARS/Ebola exposure and increased suicide attempts. A preprint study reported associations between COVID-19 distress and past-month suicidal ideation. Limitations: Few studies have investigated the topic; these are of relatively low methodological quality. Conclusion: Findings support an association between previous epidemics and increased risk of suicide-related outcomes. Research is needed to investigate the impact of COVID-19 on suicide outcomes.

In the context of the Beyond Ultradeep Frontier Fields And Legacy Observations (BUFFALO) survey, we present a new analysis of the merging galaxy cluster MACS J0416.1−2403 (z = 0.397) and its parallel field using Hubble Frontier Fields (HFF) data. We measure the surface mass density from a weak-lensing analysis and characterize the overall matter distribution in both the cluster and parallel fields. The surface mass distribution derived for the parallel field shows clumpy overdensities connected by filament-like structures elongated in the direction of the cluster core. We also characterize the X-ray emission in the parallel field and compare it with the lensing mass distribution. We identify five mass peaks at the >5σ level over the two fields, four of them being in the cluster one. Three of them are located close to galaxy overdensities and one is also close to an excess in the X-ray emission. Nevertheless, two of them have neither optical nor X-ray counterpart and are located close to the edges of the field of view, thus further studies are needed to confirm them as substructures. Finally, we compare our results with the predicted subhalo distribution of one of the Hydrangea/C-EAGLE simulated cluster. Significant differences are obtained suggesting the simulated cluster is at a more advanced evolutionary stage than MACS J0416.1−2403. Our results anticipate the upcoming BUFFALO observations that will link the two HFF fields, extending further the HST coverage. ; This project has received funding from the European Union's Horizon 2020 Research and Innovation Programme under the Marie Sklodowska-Curie grant agreement No 734374. This work was partially supported by the Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET, Argentina) and the Secretaría de Ciencia y Tecnología de la Universidad Nacional de Córdoba (SeCyT-UNC, Argentina). MJ is supported by the United Kingdom Research and Innovation (UKRI) Future Leaders Fellowship 'Using Cosmic Beasts to uncover the Nature of Dark Matter' (grant number MR/S017216/1). This project was also supported by the Science and Technology Facilities Council [grant number ST/L00075X/1]. DH is supported by the D-ITP consortium, a program of the Netherlands Organization for Scientific Research (NWO) that is funded by the Dutch Ministry of Education, Culture and Science (OCW). MS is supported by the Netherlands Organization for Scientific Research (NWO) VENI grant 639.041.749. ; Peer reviewed