Our paper studies how the nationwide expansion of bank branches affects the performance of informal microenterprises. We exploit the Branch Authorization Policy (BAP) in India, which directed banks to open branches in "underbanked" districts. Using a regression discontinuity design, we find that microenterprises in underbanked districts report higher value-addition, revenues, and productive assets, but no increase in local registration. However, borrowings on the enterprise balance sheet do not increase. The household balance sheet offers a second perspective that reconciles these findings: households in underbanked districts increased their bank borrowings for non-farm business by an amount comparable to the increase in microenterprise productive assets. Micro-entrepreneurs thus accessed bank credit as households rather than as enterprises, weakening a key incentive to formalize and helping explain how expanded access to finance can coexist with persistent informality.
Historical and ethnographic evidence suggests that people around the world use supernatural beliefs to explain misfortune. The cross-cultural prevalence of this pattern may arise from our expectations that norm violations lead to sanctioning. In cases where an outcome seems punitive yet lacks an identifiable cause, individuals, motivated to fill this explanatory gap, may rely on beliefs in supernatural punishment to make sense of what has happened. If true, supernatural explanations for misfortunes should be more common when a victim is believed to have not cooperated in the past (i.e., in cases where misfortunes might be unexplained but otherwise appear deserved). Using a vignette experiment across nine diverse populations (N = 714), including African hunter-gatherers and Melanesian horticulturalists, we tested if knowledge of past bad actions increased participants' endorsements of supernatural causes for misfortune. Across all populations, participants rated a misfortune as more likely to be supernaturally caused when the victim was known to have failed to reciprocate a favour or engage in generous actions towards others in the past. This was slightly increased when the behaviour was additionally labelled normative. Responses to open-ended free-listing questions provide additional evidence that when the victim was known to be uncooperative, participants were more likely to propose supernatural causes for misfortune as well as supernatural solutions. Additional normative labelling had only a small effect. Together, these findings suggest that when misfortunes lack clear causes, people's motivation to explain interacts with moral evaluations, leading them to invoke supernatural beliefs most commonly when misfortune appears deserved.
Ecological connectivity models commonly derive resistance surfaces from habitat suitability; however, it remains unclear how two-dimensional (2D) versus three-dimensional (3D) representations of landscape propagate through this modeling pipeline, particularly in urban environments. This study evaluated the sensitivity of habitat suitability and connectivity outputs derived from these models to the inclusion of 3D landscape structure for two bird species with contrasting habitat associations, the Western Bluebird (Sialia mexicana) and Acorn Woodpecker (Melanerpes formicivorus), in Los Angeles, California, USA. Species distribution models were developed in Maxent using 2D variables and compared to models incorporating 3D variables derived from LiDAR, with connectivity modeled using Omniscape under identical parameterization. Across both species, 2D and 3D Maxent models exhibited similar performance and high niche overlap, indicating limited sensitivity of overall habitat suitability patterns to the inclusion of 3D variables. Likewise, connectivity outputs were highly correlated with high-connectivity values consistently concentrated in protected open spaces, mirroring the patterns seen in the Maxent models. However, the inclusion of 3D variables altered variable importance in the models and produced discernible shifts in spatial configuration of some suitability and high connectivity values, with species-specific differences. The results suggest that even when overall habitat suitability and downstream connectivity outputs are similar, the inclusion of 3D variables still produced discernible differences in the spatial configuration of high connectivity values, having implications for conservation management decisions. More broadly, these results underscore the importance of evaluating how upstream modeling choices related to the dimensional characterization of landscape propagate through connectivity workflows.
A growing body of criminological research centers on the "future self," examining how young people link their present behavior to who they would like to become. Within juvenile justice, evidence suggests that the more clearly youth can imagine their futures, the more likely they are to make thoughtful, goal-directed choices that reduce delinquency. However, little is known about how justice-involved youth envision their future selves. This study draws on narrative stories written by 277 youth in a short-term juvenile detention facility in the southwestern United States, collected through the social learning platform Journey.do. Leveraging the lens of narrative criminology, an inductive thematic analysis identified four main recurring theme categories from youth responses: (1) Values That Guide Career Choices; (2) Personal Improvement Goals; (3) Family Participation; and (4) Educational Goals. The findings indicate that youth in detention hold optimistic future aspirations in several spheres of life that the system should utilize to promote desistance and positive outcomes. Areas for future research and policy, such as elevating youths' voices and redesigning system opportunities to support their idealized and individualized future selves, are discussed.
We present PhysInOne , a large-scale synthetic dataset addressing the critical scarcity of physically-grounded training data for AI systems. Unlike existing datasets limited to merely hundreds or thousands of examples, PhysInOne provides 1.4 million videos across 129,400 dynamic 3D scenes, covering 68 basic physical phenomena in mechanics, optics, fluid dynamics, and magnetism. Distinct from previous works, our scenes feature multiobject interactions against complex backgrounds, with comprehensive ground-truth annotations including 3D geometry, semantics, dynamic motion, physical properties, and text descriptions. We demonstrate PhysInOne’s efficacy across four emerging applications: physics-aware video generation, long-/short-term future frame prediction, physical property estimation, and motion transfer. Experiments show that fine-tuning foundation models on PhysInOne significantly enhances physical plausibility, while also exposing critical gaps in modeling complex physical dynamics and estimating intrinsic properties. As the largest dataset of its kind, orders of magnitude beyond prior works, PhysInOne establishes a new benchmark for advancing physics-grounded world models in generation, simulation, and embodied AI.
