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Scientific evidence regularly guides policy decisions1, with behavioural science increasingly part of this process2. In April 2020, an influential paper3proposed 19 policy recommendations (‘claims’) detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms ‘physical distancing’ and ‘social distancing’. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization.

In recent years, scholars from different fields have studied the effects of scarcity on social behaviour, producing mixed findings. This review synthesizes the most recent literature on the topic and proposes a framework to organize the evidence. According to this framework, scarcity produces an attentional shift towards the scarce resource and a cognitive load that triggers heuristic thinking; this affects social behaviour in various ways, depending on individual and contextual factors, which can be transient (e.g., emotional states or social expectations), or enduring (e.g., personality or social environment). We then apply this framework to explain when and how scarcity influences parochialism. We conclude with a caution against the uncritical use of scarcity salience as a tool for social behavioural change.

Do people discriminate between men and women when they have the option to punish defectors or reward cooperators? Here, we report on four pre-registered experiments that shed some light on this question. Study 1 (N= 544) shows that people do not discriminate between genders when they have the option to punish (reward) defectors (cooperators) in a one-shot prisoner’s dilemma with third-party punishment/reward. Study 2 (N= 253) extends Study 1 to a different method of punishing/rewarding: participants are asked to rate the behaviour of a defector/cooperator on a scale of 1–5 stars. In this case too, we find that people do not discriminate between genders. Study 3a (N= 331) and Study 3b (N= 310) conceptually replicate Study 2 with a slightly different gender manipulation. These latter studies show that, in situations where they do not have specific beliefs about the gender of the defector/cooperator’s partner, neither men nor women discriminate between genders.

Understanding human behaviour in decision problems and strategic interactions has wide-ranging applications in economics, psychology and artificial intelligence. Game theory offers a robust foundation for this understanding, based on the idea that individuals aim to maximize a utility function. However, the exact factors influencing strategy choices remain elusive. While traditional models try to explain human behaviour as a function of the outcomes of available actions, recent experimental research reveals that linguistic content significantly impacts decision-making, thus prompting a paradigm shift from outcome-based to language-based utility functions. This shift is more urgent than ever, given the advancement of generative AI, which has the potential to support humans in making critical decisions through language-based interactions. We propose sentiment analysis as a fundamental tool for this shift and take an initial step by analysing 61 experimental instructions from the dictator game, an economic game capturing the balance between self-interest and the interest of others, which is at the core of many social interactions. Our meta-analysis shows that sentiment analysis can explain human behaviour beyond economic outcomes. We discuss future research directions. We hope this work sets the stage for a novel game-theoretical approach that emphasizes the importance of language in human decisions.

We explore whether priming emotion versus deliberation affects speciesism—the tendency to prioritize certain individuals over others on the basis of their species membership (three main and two supplementary studies, four preregistered; N= 3,288). We find that the tendency to prioritize humans over animals (anthropocentric speciesism) decreaseswhen participants were asked to think emotionally compared to deliberatively. In contrast, the tendency to prioritize dogs over other animals (pet speciesism) increaseswhen participants were asked to think emotionally compared to deliberatively. We hypothesize that, emotionally, people like animals in general and dogs in particular; however, deliberatively, people attribute higher moral status to humans than animals and roughly equal status to dogs, chimpanzees, elephants, and pigs. In support of this explanation, participants tended to discriminate between animals based on likability when thinking emotionally and based on moral status when thinking deliberatively. These findings shed light on the psychological underpinnings of speciesism.

•Whether honesty is intuitive or requires deliberation is a current topic of debate.•Previous studies found mixed results.•We show that time pressure increases honesty in a deception game.•Our results are not driven by confounds present in previous work.

•Previous research shows that the mere act of considering one's strategic options (i.e., looking at payoffs) will be met with distrust by observers.•Here we aim at extending this finding by changing the measure of pro-sociality: instead of trustworthiness, we look at altruism.•Two experiments uncover a perception gap according to which looking at payoffs signals selfish behavior, but it does not actually mean so.•Specifically, “lookers” are believed to be less altruist than “non-lookers”, but their actual level of altruism is not different from that of “non-lookers”.

Abstract: We define the isoperimetric constant for any locally finite metric space and we study the property of having isoperimetric constant equal to zero. This property, called Small Neighborhood property, clearly extends amenability to any locally finite space. Therefore, we start making a comparison between this property and other notions of amenability for locally finite metric spaces that have been proposed by Gromov, Lafontaine and Pansu, by Ceccherini-Silberstein, Grigorchuk and de la Harpe and by Block and Weinberger. We discuss possible applications of the property SN in the study of embedding a metric space into another one. In particular, we propose three results: we prove that a certain class of metric graphs that are isometrically embeddable into Hilbert spaces must have the property SN. We also show, by a simple example, that this result is not true replacing property SN with amenability. As a second result, we prove that many spaces with uniform bounded geometry having a bi-lipschitz embedding into Euclidean spaces must have the property SN. Finally, we prove a Bourgain-like theorem for metric trees: a metric tree with uniform bounded geometry and without property SN does not have bi-lipschitz embeddings into finite-dimensional Hilbert spaces. [Copyright &y& Elsevier]

One-shot anonymous unselfishness in economic games is commonly explained by social preferences, which assume that people care about the monetary pay-offs of others. However, during the last 10 years, research has shown that different types of unselfish behaviour, including cooperation, altruism, truth-telling, altruistic punishment and trustworthiness are in fact better explained by preferences for following one's own personal norms—internal standards about what is right or wrong in a given situation. Beyond better organizing various forms of unselfish behaviour, this moral preference hypothesis has recently also been used to increase charitable donations, simply by means of interventions that make the morality of an action salient. Here we review experimental and theoretical work dedicated to this rapidly growing field of research, and in doing so we outline mathematical foundations for moral preferences that can be used in future models to better understand selfless human actions and to adjust policies accordingly. These foundations can also be used by artificial intelligence to better navigate the complex landscape of human morality.

•Recent work in the Prisoners’ dilemma highlights that cooperation may be due to moral preferences.•We provide data from a large pre-registered, experiment to study motives for cooperation in the Stag-Hunt game (SHG).•We find that cooperation in the SHG is primarily driven by preferences for efficiency, rather than moral preferences.