Project description:In 11 studies, we found that participants typically did not enjoy spending 6 to 15 minutes in a room by themselves with nothing to do but think, that they enjoyed doing mundane external activities much more, and that many preferred to administer electric shocks to themselves instead of being left alone with their thoughts. Most people seem to prefer to be doing something rather than nothing, even if that something is negative.
Project description:Heavy geographic patterning to the 2016 Brexit vote in UK and Trump vote in US has resulted in numerous ecological analyses of variations in area-level voting behaviours. We extend this work by employing modelling approaches that permit regionally-specific associations between outcome and explanatory variables. We do so by generating a large number of regional models using penalised regression for variable selection and coefficient evaluation. The results reinforce those already published in that we find associations in support of a 'left-behind' reading. Multivariate models are dominated by a single variable-levels of degree-education. Net of this effect, 'secondary' variables help explain the vote, but do so differently for different regions. For Brexit, variables relating to material disadvantage, and to a lesser extent structural-economic circumstances, are more important for regions with a strong industrial history than for regions that do not share such a history. For Trump, increased material disadvantage reduces the vote both in global models and models built mostly for Southern states, thereby undermining the 'left-behind' reading. The reverse is nevertheless true for many other states, particularly those in New England and the Mid-Atlantic, where comparatively high levels of disadvantage assist the Trump vote and where model outputs are more consistent with the UK, especially so for regions with closer economic histories. This pattern of associations is exposed via our regional modelling approach, application of penalised regression and use of carefully designed visualization to reason over 100+ model outputs located within their spatial context. Our analysis, documented in an accompanying github repository, is in response to recent calls in empirical Social and Political Science for fuller exploration of subnational contexts that are often controlled out of analyses, for use of modelling techniques more robust to replication and for greater transparency in research design and methodology.
Project description:Offspring of individuals with psychoses sometimes display an abnormal development of cognition, language, motor performance, social adaptation, and emotional functions. The aim of this study was to investigate the ability of children of mothers with schizophrenia (n = 28) and bipolar disorder (n = 23) to understand mental states of others using the Eyes Test (folk psychology or "theory of mind") and physical causal interactions of inanimate objects (folk physics). Compared with healthy controls (n = 29), the children of mothers with schizophrenia displayed significantly impaired performances on the Eyes Test but not on the folk physics test when corrected for IQ. The children of mothers with bipolar disorder did not differ from the controls. The folk physics test showed a significant covariance with IQ, whereas the Eyes Test did not exhibit such covariance. These results suggest that the attribution of mental states, but not the interpretation of causal interaction of objects, is impaired in offspring of individuals with schizophrenia, which may contribute to social dysfunctions.
Project description:Using data from the 2012 International Social Survey Program (n = 8,269), this study investigated how couples integrate and manage their income across 20 countries with varying degrees of gender inequality. Couples were more likely to report that one person managed the shared pot of money in countries with high gender inequality compared with couples in more gender equal countries. This pattern was not moderated by within-couple earnings equality. We found a cohabitation-marriage gap in income arrangements that is largest where national-level gender equality is high. In more gender equal contexts, married couples were more likely to pool and manage their money together, whereas a larger proportion of married couples assigned one money manager in countries with less gender equality. Cohabiting couples were more likely to keep some money separate than to take-up a pooled, jointly managed approach in more gender equal countries. Findings demonstrate the need to consider both management and pooling dimensions of couples' treatment of money to understand the influence of contextual factors on couples' income arrangements.
Project description:To determine the reproducibility of psychological meta-analyses, we investigated whether we could reproduce 500 primary study effect sizes drawn from 33 published meta-analyses based on the information given in the meta-analyses, and whether recomputations of primary study effect sizes altered the overall results of the meta-analysis. Results showed that almost half (k = 224) of all sampled primary effect sizes could not be reproduced based on the reported information in the meta-analysis, mostly because of incomplete or missing information on how effect sizes from primary studies were selected and computed. Overall, this led to small discrepancies in the computation of mean effect sizes, confidence intervals and heterogeneity estimates in 13 out of 33 meta-analyses. We provide recommendations to improve transparency in the reporting of the entire meta-analytic process, including the use of preregistration, data and workflow sharing, and explicit coding practices.
Project description:Microbiota-associated metabolic reprograming influenced clinical outcome in the randomized dendritic cell-based clinical trial in stage III melanoma
Project description:Crises like COVID-19 exposed the fragility of highly interdependent corporate supply networks and the complex production processes depending on them. However, a quantitative assessment of individual companies' impact on the networks' overall production is hitherto non-existent. Based on a unique value added tax dataset, we construct the firm-level production network of an entire country at an unprecedented granularity and present a novel approach for computing the economic systemic risk (ESR) of all firms within the network. We demonstrate that 0.035% of companies have extraordinarily high ESR, impacting about 23% of the national economic production should any of them default. Firm size cannot explain the ESR of individual companies; their position in the production networks matters substantially. A reliable assessment of ESR seems impossible with aggregated data traditionally used in Input-Output Economics. Our findings indicate that ESR of some extremely risky companies can be reduced by introducing supply chain redundancies and changes in the network topology.
Project description:Trees sustain livelihoods and mitigate climate change but a predominance of trees outside forests and limited resources make it difficult for many tropical countries to conduct automated nation-wide inventories. Here, we propose an approach to map the carbon stock of each individual overstory tree at the national scale of Rwanda using aerial imagery from 2008 and deep learning. We show that 72% of the mapped trees are located in farmlands and savannas and 17% in plantations, accounting for 48.6% of the national aboveground carbon stocks. Natural forests cover 11% of the total tree count and 51.4% of the national carbon stocks, with an overall carbon stock uncertainty of 16.9%. The mapping of all trees allows partitioning to any landscapes classification and is urgently needed for effective planning and monitoring of restoration activities as well as for optimization of carbon sequestration, biodiversity and economic benefits of trees.