Twenty questions about design behavior for sustainability, report of the International Expert Panel on behavioral science for design

How behavioral scientists, engineers, and architects can work together to advance how we all understand and practice design—in order to enhance sustainability in the built environment, and beyond.https://www.nature.com/documents/design_behavior_for_sustainability.pdfPublished versio

Regulating Complacency: Human Limitations and Legal Efficacy

This Article examines how insights into limited human rationality can improve financial regulation. The Article identifies four categories of limitations—herd behavior, cognitive biases, overreliance on heuristics, and a proclivity to panic—that undermine the perfect-market regulatory assumptions that parties have full information and will act in their rational self-interest. The Article then analyzes how insights into these limitations can be used to correct resulting market failures. Requiring more robust disclosure and due diligence, for example, can help to reduce reliance on misleading information cascades that motivate herd behavior. Debiasing through law, such as requiring more specific, poignant, and concrete disclosure of risks and their consequences, can help to correct cognitive biases. Requiring firms to engage in more self-aware operational risk management and reporting can reduce the likelihood that parties will over-rely on heuristics. And legislating backstop market liquidity and other stabilizing controls can help to minimize panics. Regulation, however, can only partly overcome these limitations. Effective financial regulation should therefore be designed not only to address these limitations but also to try to mitigate the harm of inevitable financial failures

Overestimating HIV infection:

In the absence of HIV testing, how do rural Malawians assess their HIV status? In this paper, we use a unique dataset that includes respondents’ HIV status as well as their subjective likelihood of HIV infection. These data show that many rural Malawians overestimate their likelihood of current HIV infection. The discrepancy between actual and perceived status raises an important question: Why are so many wrong? We begin by identifying determinants of self-assessed HIV status, and then compare these assessments with HIV biomarker results. Finally, we ask what characteristics of individuals are associated with errors in self-assessments.accuracy of perceived HIV status, AIDS/HIV, perceived risk, Sub-Saharan Africa

Regulating Complacency: Human Limitations and Legal Efficacy

This Article examines how insights into limited human rationality can improve financial regulation. The Article identifies four categories of limitations—herd behavior, cognitive biases, overreliance on heuristics, and a proclivity to panic—that undermine the perfect-market regulatory assumptions that parties have full information and will act in their rational self-interest. The Article then analyzes how insights into these limitations can be used to correct resulting market failures. Requiring more robust disclosure and due diligence, for example, can help to reduce reliance on misleading information cascades that motivate herd behavior. Debiasing through law, such as requiring more specific, poignant, and concrete disclosure of risks and their consequences, can help to correct cognitive biases. Requiring firms to engage in more self-aware operational risk management and reporting can reduce the likelihood that parties will over-rely on heuristics. And legislating backstop market liquidity and other stabilizing controls can help to minimize panics. Regulation, however, can only partly overcome these limitations. Effective financial regulation should therefore be designed not only to address these limitations but also to try to mitigate the harm of inevitable financial failures

Post-processing partitions to identify domains of modularity optimization

We introduce the Convex Hull of Admissible Modularity Partitions (CHAMP) algorithm to prune and prioritize different network community structures identified across multiple runs of possibly various computational heuristics. Given a set of partitions, CHAMP identifies the domain of modularity optimization for each partition ---i.e., the parameter-space domain where it has the largest modularity relative to the input set---discarding partitions with empty domains to obtain the subset of partitions that are "admissible" candidate community structures that remain potentially optimal over indicated parameter domains. Importantly, CHAMP can be used for multi-dimensional parameter spaces, such as those for multilayer networks where one includes a resolution parameter and interlayer coupling. Using the results from CHAMP, a user can more appropriately select robust community structures by observing the sizes of domains of optimization and the pairwise comparisons between partitions in the admissible subset. We demonstrate the utility of CHAMP with several example networks. In these examples, CHAMP focuses attention onto pruned subsets of admissible partitions that are 20-to-1785 times smaller than the sets of unique partitions obtained by community detection heuristics that were input into CHAMP.Comment: http://www.mdpi.com/1999-4893/10/3/9