Theories of the deep: combining salience and network analyses to produce mental model visualizations of a coastal British Columbia food web

Arriving at shared mental models among multiple stakeholder groups can be crucial for successful management of contested social-ecological systems (SES). Academia can help by first eliciting stakeholders’ initial, often tacit, beliefs about a SES, and representing them in useful ways. We demonstrate a new recombination of techniques for this purpose, focusing specifically on tacit beliefs about food webs. Our approach combines freelisting and sorting techniques, salience analysis, and ultimately network analysis, to produce accessible visualizations of aggregate mental models that can then be used to facilitate discussion or generate further hypotheses about cognitive drivers of conflict. The case study we draw upon to demonstrate this technique is Clayoquot Sound UNESCO Biosphere Reserve, on the west coast of British Columbia, Canada. There, an immanent upsurge in the sea otter (Enhydra lutris) population, which competes with humans for shellfish, has produced tension among government managers, and both First Nations and non-First Nations residents. Our approach helps explain this tension by visually highlighting which trophic relationships appear most cognitively salient among the lay public. We also include speculative representations of models held by managers, and pairs of contrasting demographic subgroups, to further demonstrate potential uses of the method

Overconfidence is universal? Elicitation of genuine overconfidence (EGO) procedure reveals systematic differences across domain, task knowledge, and incentives in four populations

Overconfidence is sometimes assumed to be a human universal, but there remains a dearth of data systematically measuring overconfidence across populations and contexts. Moreover, cross-cultural experiments often fail to distinguish between placement and precision and worse still, often compare population-mean placement estimates rather than individual performance subtracted from placement. Here we introduce a procedure for concurrently capturing both placement and precision at an individual level based on individual performance: The Elicitation of Genuine Overconfidence (EGO) procedure. We conducted experiments using the EGO procedure, manipulating domain, task knowledge, and incentives across four populations—Japanese, Hong Kong Chinese, Euro Canadians, and East Asian Canadians. We find that previous measures of population-level overconfidence may have been misleading; rather than universal, overconfidence is highly context dependent. Our results reveal cross-cultural differences in sensitivity to incentives and differences in overconfidence strategies, with underconfidence, accuracy, and overconfidence. Comparing sexes, we find inconsistent results for overplacement, but that males are consistently more confident in their placement. These findings have implications for our understanding of the adaptive value of overconfidence and its role in explaining population-level and individual-level differences in economic and psychological behavior

Understanding cumulative cultural evolution

This is the final version of the article. Available from the publisher via the DOI in this record.No abstract availabl

Beyond Western, educated, industrial, rich, and democratic (WEIRD) psychology: measuring and mapping scales of cultural and psychological distance

In this article, we present a tool and a method for measuring the psychological and cultural distance between societies and creating a distance scale with any population as the point of comparison. Because psychological data are dominated by samples drawn from Western, educated, industrialized, rich, and democratic (WEIRD) nations, and overwhelmingly, the United States, we focused on distance from the United States. We also present distance from China, the country with the largest population and second largest economy, which is a common cultural comparison. We applied the fixation index (FST), a meaningful statistic in evolutionary theory, to the World Values Survey of cultural beliefs and behaviors. As the extreme WEIRDness of the literature begins to dissolve, our tool will become more useful for designing, planning, and justifying a wide range of comparative psychological projects. Our code and accompanying online application allow for comparisons between any two countries. Analyses of regional diversity reveal the relative homogeneity of the United States. Cultural distance predicts various psychological outcomes

Unsupervised machine learning for transient discovery in deeper, wider, faster light curves

Identification of anomalous light curves within time-domain surveys is often challenging. In addition, with the growing number of wide-field surveys and the volume of data produced exceeding astronomers’ ability for manual evaluation, outlier and anomaly detection is becoming vital for transient science. We present an unsupervised method for transient discovery using a clustering technique and the ASTRONOMALY package. As proof of concept, we evaluate 85 553 min-cadenced light curves collected over two ∼1.5 h periods as part of the Deeper, Wider, Faster program, using two different telescope dithering strategies. By combining the clustering technique HDBSCAN with the isolation forest anomaly detection algorithm via the visual interface of ASTRONOMALY, we are able to rapidly isolate anomalous sources for further analysis. We successfully recover the known variable sources, across a range of catalogues from within the fields, and find a further seven uncatalogued variables and two stellar flare events, including a rarely observed ultrafast flare (∼5 min) from a likely M-dwarf

Four years of Type Ia Supernovae Observed by TESS: Early Time Light Curve Shapes and Constraints on Companion Interaction Models

We present 307 Type Ia supernova (SN) light curves from the first four years of the TESS mission. We use this sample to characterize the shapes of the early time light curves, measure the rise times from first light to peak, and search for companion star interactions. Using simulations, we show that light curves must have noise $<$10% of the peak to avoid biases in the early time light curve shape, restricting our quantitative analysis to 74 light curves. We find that the mean power law index $t^{\beta_1}$ of the early time light curves is 1.83$\pm$ 0.57 and the mean rise time to peak is 15.7 $\pm$ 3.5 days. We also estimate the underlying population distribution and find a Gaussian component with mean $\beta_1 = 2.29$, width 0.34, and a tail extending to values less than 1.0. We use model comparison techniques to test for the presence of companion interactions. In contrast to recent results in the literature, we find that the data can rarely distinguish between models with and without companion interactions, and caution is needed when claiming detections of early time flux excesses. Nevertheless, we find three high-quality SN light curves that tentatively prefer the addition of a companion interaction model, but the statistical evidence is not robust. We also find two SNe that disfavor the addition of a companion interaction model to a curved power law model. Taking the 74 SNe together, we calculate 3$\sigma$ upper limits on the presence of companion signatures to control for orientation effects that can hide companions in individual light curves. Our results rule out common progenitor systems with companions having Roche lobe radii $>$ 31 R$_{\odot}$ (99.9% confidence level) and disfavor companions having Roche lobe radii $>$ 10 R$_{\odot}$ (95% confidence level). Lastly, we discuss the implications of our results for the intrinsic fraction of single degenerate progenitor systems.Comment: 40 pages, 23 figures, resubmitted to ApJ. Figure sets for all 307 objects in Figures 3, 13, 14, and 16, can be viewed at https://space.mit.edu/home/faus/snIa_fig_sets/ in advance of the online journal articl