https://www.mdu.se/

When someone violates a social norm, others may think that some sanction would be appropriate. We examine how the experience of emotions like anger and disgust relate to the judged appropriateness of sanctions, in a pre-registered analysis of data from a large-scale study in 56 societies. Across the world, we find that individuals who experience anger and disgust over a norm violation are more likely to endorse confrontation, ostracism and, to a smaller extent, gossip. Moreover, we find that the experience of anger is consistently the strongest predictor of judgments of confrontation, compared to other emotions. Although the link between state-based emotions and judgments may seem universal, its strength varies across countries. Aligned with theoretical predictions, this link is stronger in societies, and among individuals, that place higher value on individual autonomy. Thus, autonomy values may increase the role that emotions play in guiding judgments of social sanctions.

Did cultures change shortly after, and in response to, the COVID-19 outbreak? If so, then in what way? We study these questions for a set of macro-cultural dimensions: collectivism/individualism, duty/joy, traditionalism/autonomy, and pro-fertility/individual-choice norms. We also study specific perceptions and norms like perceived threats to society (e.g. immigration) and hygiene norms. We draw on Evolutionary Modernization Theory, Parasite Stress Theory, and the Behavioural Immune System, and existing evidence, to make an overarching prediction: the COVID-19 pandemic should increase collectivism, duty, traditionalism, conformity (i.e. pro-fertility), and outgroup prejudice. We derive specific hypotheses from this prediction and use survey data from 29,761 respondents, in 55 cities and 43 countries, collected before (April–December 2019) and recently after the emergence of COVID-19 (April–June 2020) to test them. We exploit variation in disease intensity across regions to test potential mechanisms behind any changes. The macro-cultural dimensions remained stable. In contrast, specific perceptions and norms related to the pandemic changed: norms of hygiene substantially increased as did perceived threats related to disease. Taken together, our findings imply that macro-cultural dimensions are primarily stable while specific perceptions and norms, particularly those related to the pandemic, can change rapidly. Our findings provide new evidence for theories of cultural change and have implications for policy, public health, daily life, and future trajectories of our societies.

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, suddenly erupted in China at the beginning of 2020 and soon spread worldwide. This has resulted in an outstanding increase on research about the virus itself and, more in general, epidemics in many scientific fields. In this work we focus on the dynamics of the epidemic spreading and how it can be affected by the individual variability in compliance with social norms, i.e. in the adoption of preventive social norms by population's members, which influences the infectivity rate throughout the population and through time. By means of theoretical considerations, we show how such heterogeneities of the infection rate make the population more resistant against the epidemic spreading. Finally, we depict possible empirical tests aimed to confirm our results.

In social interactions, human decision-making, attitudes, and beliefs about others coevolve. Their dynamics are affected by cost-benefit considerations, cognitive processes (such as cognitive dissonance, social projecting, and logic constraints), and social influences by peers (via descriptive and injunctive social norms) and by authorities (e.g., educational, cultural, religious, political, administrative, individual or group, real or fictitious). Here we attempt to disentangle some of this complexity by using an integrative mathematical modeling and a 35-day online behavioral experiment. We utilize data from a Common Pool Resources experiment with or without messaging promoting a group-beneficial level of resource extraction. We directly estimate the weights of different factors in decision-making and beliefs dynamics. We show that personal norms and conformity with expected peers’ actions have the largest impact on decision-making while material benefits and normative expectations have smaller effects. Individuals behaving prosocially are characterized by higher weights of personal norms while antisocial types are more affected by conformity. Messaging greatly decreases the weight of personal norms while simultaneously increases the weight of conformity. It also markedly influences personal norms and normative expectations. Both cognitive and social factors are important in the dynamics of beliefs. Between-individual variation is present in all measured characteristics and notably impacts observed group behavior. At the same time, gender differences are small. We argue that one can hardly understand social behavior without understanding the dynamics of personal beliefs and beliefs about others and that cognitive, social, and material factors all play important roles in these processes. Our results have implications for understanding and predicting social processes triggered by certain shocks (e.g., social unrest, a pandemic, or a natural disaster) and for designing policy interventions aiming to change behavior (e.g., actions aimed at environment protection or climate change mitigation).

Social norms have been investigated across many disciplines for many years, but until recently, studies mainly provided indirect, implicit and correlational support for the role of social norms in driving behaviour. To understand how social norms, and in particular social norm change, can generate a large-scale behavioural change to deal with some of the most pressing challenges of our current societies, such as climate change and vaccine hesitancy, we discuss and review several recent advances in social norm research that enable a more precise underpinning of the role of social norms: how to identify their existence, how to establish their causal effect on behaviour and when norm change may pass tipping points. We advocate future research on social norms to study norm change through a mechanism-based approach that integrates experimental and computational methods in theory-driven, empirically calibrated agent-based models. As such, social norm research may move beyond unequivocal praising of social norms as the missing link between self-interested behaviour and observed cooperation or as the explanation for (the lack of) social tipping. It provides the toolkit to understand explicitly where, when and how social norms can be a solution to solve large-scale problems, but also to recognize their limits.This article is part of the theme issue 'Emergent phenomena in complex physical and socio-technical systems: from cells to societies'.

Social norms regulate our behavior in a variety of mundane and far-reaching contexts, from tipping at the restaurant to social distancing during a pandemic. However, how social norms emerge, persist, and change is still poorly understood. Here the authors investigate experimentally whether spontaneously emerging behavioral regularities (i.e., conventions) gain normativity over time and, if so, whether their normative underpinning makes them resistant to changes in economic incentives. To track the coevolution of behavior and normativity, the authors use a set of measures to elicit participants' first- and second-order normative beliefs and their (dis)approval of other participants' behaviors. The authors find that even in the limited duration of their lab experiment, conventions gain normativity that makes these conventions resistant to change, especially if they promote egalitarian outcomes and the change in economic incentives is relatively small. These findings advance our understanding of how cognitive, social and economic mechanisms interact in bringing about social change.

Objectives We test the effects of four policy scenarios on recruitment into organized crime. The policy scenarios target (i) organized crime leaders and (ii) facilitators for imprisonment, (iii) provide educational and welfare support to children and their mothers while separating them from organized-crime fathers, and (iv) increase educational and social support to at-risk schoolchildren. Methods We developed a novel agent-based model drawing on theories of peer effects (differential association, social learning), social embeddedness of organized crime, and the general theory of crime. Agents are simultaneously embedded in multiple social networks (household, kinship, school, work, friends, and co-offending) and possess heterogeneous individual attributes. Relational and individual attributes determine the probability of offending. Co-offending with organized crime members determines recruitment into the criminal group. All the main parameters are calibrated on data from Palermo or Sicily (Italy). We test the effect of the four policy scenarios against a baseline no-intervention scenario on the number of newly recruited and total organized crime members using Generalized Estimating Equations models. Results The simulations generate realistic outcomes, with relatively stable organized crime membership and crime rates. All simulated policy interventions reduce the total number of members, whereas all but primary socialization reduce newly recruited members. The intensity of the effects, however, varies across dependent variables and models. Conclusions Agent-based models effectively enable to develop theoretically driven and empirically calibrated simulations of organized crime. The simulations can fill the gaps in evaluation research in the field of organized crime and allow us to test different policies in different environmental contexts.

Criminalorganizationsexploittheirpresenceonterritories and local communities to recruit new workforce in order to carry out their criminal activities and business. The ability to attract individuals is crucial for maintaining power and control over the territories in which these groups are settled. This study proposes the formalization, development and analysis of an agent-based model (ABM) that simulates a neighborhood of Palermo (Sicily) with the aim to understand the pathways that lead individuals to recruitment into organized crime groups (OCGs). Using empirical data on social, economic and criminal conditions of the area under analysis, we use a multi-layer network approach to simulate this scenario. As the final goal, we test different policies to counter recruitment into OCGs. These scenarios are based on two different dimensions of prevention and intervention: (i) primary and secondary socialization and (ii) law enforcement targeting strategies.

The original version of this Article contained an error in the author affiliations. Cecilia Reyna was incorrectly associated with ‘Universidad Nacional de Córdoba (UNC). Facultad de Psicología (UNC), Ciudad Universitaria, Bv. de la Reforma esquina, Enfermera Gordillo s/n, Córdoba, Argentina.’ instead of the correct ‘Instituto de Investigaciones Psicológicas (IIPsi), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), CABA, República Argentina.’ This has now been corrected in both the PDF and HTML versions of the Article. © The Author(s) 2021

Social norms can help solve pressing societal challenges, from mitigating climate change toreducing the spread of infectious diseases. Despite their relevance, how norms shape cooperation among strangers remains insufficiently understood. Influential theories also suggest that the level of threat faced by different societies plays a key role in the strength ofthe norms that cultures evolve. Still little causal evidence has been collected. Here we deal with this dual challenge using a 30-day collective-risk social dilemma experiment to measure norm change in a controlled setting. We ask whether a looming risk of collective loss increases the strength of cooperative social norms that may avert it. We find that social norms predict cooperation, causally affect behavior, and that higher risk leads to stronger social norms that are more resistant to erosion when the risk changes. Taken together, our results demonstrate the causal effect of social norms in promoting cooperation and their role in making behavior resilient in the face of exogenous change.