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ObjectivesWe 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.MethodsWe 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.ResultsThe 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.ConclusionsAgent-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.

From inmates in prison gangs to soldiers in elite units, the intimidating reputation of groups often precedes its members. While individual reputation is known to affect people’s aggressiveness, whether one’s group reputation can similarly influence behavior in conflict situations is yet to be established. Using an economic game experiment, we isolate the effect of group reputation on aggression and conflict from that of individual reputation. We find that group reputation can increase the willingness to inflict costs on others but only when individuals are able to punish their fellow members. Even if internal discipline can sustain their shared reputation, more intimidating groups provide fewer benefits to their members in the short run. Using an agent-based simulation, we show that this might not be the case in the long run. Our findings yield insights into the effects of group reputation on aggression, conflict, and possible consequences for group survival.

Social norms can help solve pressing societal challenges, from mitigating climate change to reducing 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 of the 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., Large-scale cooperation is needed to reduce existential risks like those posed by pandemics and climate change. Here the authors demonstrate that social norms can emerge and sustain cooperation in situations of collective risk and that the level of risk influences the strength of the norms.

Human cooperation is both powerful and puzzling. Large-scale cooperation among genetically unrelated individuals makes humans unique with respect to all other animal species. Therefore, learning how cooperation emerges and persists is a key question for social scientists. Recently, scholars have recognized the importance of social norms as solutions to major local and large-scale collective action problems, from the management of water resources to the reduction of smoking in public places to the change in fertility practices. Yet a well-founded model of the effect of social norms on human cooperation is still lacking.We present here a version of the Experience-Weighted Attraction (EWA) reinforcement learning model that integrates norm-based considerations into its utility function that we call EWA+Norms. We compare the behaviour of this hybrid model to the standard EWA when applied to a collective risk social dilemma in which groups of individuals must reach a threshold level of cooperation to avoid the risk of catastrophe. We find that standard EWA is not sufficient for generating cooperation, but that EWA+Norms is. Next step is to compare simulation results with human behaviour in large-scale experiments.

First published online: 07 February 2020 Will fights erupt when resources are scarce and the rules regulating their distribution are absent or ignored? : We conjecture that the answer depends on whether credible information about individuals' toughness is available. When people send credible signs and signals of their toughness disputes may be solved without violence. We use a laboratory experiment in which subjects create information about their toughness and decide whether to take others' resources and resist in case others' attempt to take theirs. Subjects perform a potentially painful but safe physical exercise to create information and to determine who wins and loses fights. This, realistically, ranks subjects according to their toughness and implicates toughness, a quality important in real conflict, in fighting. We find that, consistent with theory, information reduces fighting. This suggests that, in addition to the theories traditionally used to explain prisoner behavior, the availability of credible information about toughness influences prison conflict.

We present a version of the experience-weighted attraction (EWA) reinforcement learning model that integrates norm conformity into its utility function that we call “EWA+Norms.” We compare the behavior of this hybrid model to the standard EWA when applied to a step-level public good game in which groups of agents must reach a threshold level of cooperation to avoid the risk of catastrophe. We find that standard EWA is not sufficient for generating cooperation, but that EWA+Norms is. We aim to compare simulation results with human behavior in large-scale experiments that we are currently running.

First Online: 01 September 2016 Computer simulation has recently been recognised by criminologists as a useful tool for bridging the gap between theoretical and empirical analyses of organised crime and for supplementing their weaknesses. GLODERS-S is an innovative and configurable agent-based simulator specialised in reproducing the dynamics of a specific type of criminal organisations: protection racketeering groups. The simulator adopts an event-based approach that provides a more realistic operation of the agents, which integrated with its configurability provides policy-makers with a highly flexible platform for analysing multiple scenarios and assessing policies to counter organised crime. In this paper, we describe the principles of the simulator design, its features and limitations, and possible applications.

Protection racketeering groups are powerful, deeply entrenched in multiple societies across the globe, and they harm the societies and economies in which they operate in multiple ways. These reasons make their dynamics important to understand and an objective of both scientific and application-oriented interest. Legal and social norm-based approaches arguably play significant roles in influencing protection racket dynamics. We propose an agent-based simulation model, the Palermo Scenario, to enrich our understanding of these influences and to test the effect of different policies on protection racket dynamics. Our model integrates the legal and the social norm-based approaches and uses a complex normative agent architecture that enables the analysis of both agents' behaviours and mental normative representations driving behaviour. We demonstrate the usefulness of the model and the benefits of using this complex normative architecture through a case study of the Sicilian Mafia. This work was partially supported by the FP7-ICT Science of Global Systems programme of the European Commission through Project GLODERS (http://www.gloders.eu, Global Dynamics of Extortion Racket Systems) under Grant agreement no.: 315874.

Available online 28 July 2014. When we become aware that our past actions carry information about qualities that we possess or lack, which others use to decide how to deal with us, are we unconcerned, content to rely on what we have done, or do we take action to alter this information? We study this question experimentally using generosity as a sign and a signal of trustworthiness, and a trust game. Subjects play a dictator game unaware that later they will play a trust game and that their level of generosity in the dictator game will be revealed to trusters, with some inaccuracy, before trusters decide whether to trust or not. Once made aware of what follows, trustees have the option to play a second dictator game, from which their choice will be accurately conveyed to trusters in addition to their decision in the initial game. Consistent with ‘countersignalling theory’, those who, in the first dictator game, were either miserly or generous do not play the second dictator game, resigned or content with the information conveyed by their past actions. Those neither miserly nor generous in the first dictator game, an intermediate generous group, are likeliest to use the second dictator game; many of them for the purpose of signalling, so that they are not confused with the miserly.

Even if an animal matches its surroundings perfectly in colour and texture, any mismatch between the spatial phase of its pattern and that of the background, or shadow created by its three-dimensional relief, is potentially revealing. Nevertheless, for camouflage to be fully broken, the shape must be recognizable. Disruptive coloration acts against object recognition by the use of high-contrast internal colour boundaries to break up shape and form. As well as the general outline, characteristic features such as eyes and limbs must also be concealed; this can be achieved by having the colour patterns on different, but adjacent, body parts aligned to match each other (i.e. in phase). Such ‘coincident disruptive coloration’ ensures that there is no phase disjunction where body parts meet, and causes different sections of the body to blend perceptually. We tested this theory using field experiments with predation by wild birds on artificial moth-like targets, whose wings and (edible pastry) bodies had colour patterns that were variously coincident or not. We also carried out an experiment with humans searching for analogous targets on a computer screen. Both experiments show that coincident disruptive coloration is an effective mechanism for concealing an otherwise revealing body form.

We study how communication affects cooperation in an experimental public goods environment with punishment and counter-punishment opportunities. Participants interacted over 30 rounds in fixed groups with fixed identifiers that allowed them to trace other group members' behavior over time. The two dimensions of communication we study are asking for a specific contribution level and having to express oneself when choosing to counter-punish. We conduct four experimental treatments, all involving a contribution stage, a punishment stage, and a counter-punishment stage in each round. In the first treatment communication is not possible at any of the stages. The second treatment allows participants to ask for a contribution level at the punishment stage and in the third treatment participants are required to send a message if they decide to counter-punish. The fourth combines the two communication channels of the second and third treatments. We find that the three treatments involving communication at any of the two relevant stages lead to significantly higher contributions than the baseline treatment. We find no difference between the three treatments with communication. We also relate our results to previous results from treatments without counter-punishment opportunities and do not find that the presence of counter-punishment leads to lower cooperation level. The overall pattern of results shows that given fixed identifiers the key factor is the presence of communication. Whenever communication is possible contributions and earnings are higher than when it is not, regardless of counter-punishment opportunities., The work presented in this paper has been performed in the frame of the MacNorms project (Intramurales de frontera CSIC – PIF08-007), MILESS project (Ministerio de economía y competitividad - TIN2013-45039-P - financed by FEDER) and of the GLODERS project (Seventh Framework EU Programme FP7/2007-2013 Grant: 315874).

Norms, in their many forms, are all around us. The social world that we inhabit is saturated with them. As others have elegantly put it, ‘from forceps to grave, human life is wrapped in a tightly woven tapestry of rules, standards, and expectations that govern every aspect of social behaviour’ (Anderson & Dunning, 2014). Not only are norms widespread, but they also have powerful effects on our individual and social behaviour, often for the better but sometimes for the worse (Ellickson, 1991; Fehr & Fischbacher, 2004; Henrich et al., 2001). Actions taken within the context of protection rackets are arguably not exempt. Domain-specific norms, regarding paying or supporting behaviour, and domain-general norms such as reciprocity and fairness may shape behaviour there too.

Mafias can be considered as criminal organisations that are in the business of producing, promoting, and selling protection. Here, we describe the Palermo Scenario, an agent-based model of protection rackets aimed to deepen our understanding of protection rackets, and help policymakers to evaluate methods for destabilising them. Additionally, since the system is explicitly specified, we can use it to investigate the entire causal pathway from cause to effect: not only from actions to Mafia destabilisation, but also the intermediate actions along the path and actors' internal mental representations among the population.

The aim of this chapter is to summarise the problems incurred during the phases of calibrating and validating the extortion racket models used by the GLODERS project. The chapter starts with the discussion of the data availability and summarises shortly the contents of Sect. 4.3. It continues with a discussion of what parameterisation, calibration, sensitivity analysis and validation have to do with each other and ends up with a discussion of the validity of the GLODERS models.

Mafias are highly powerful and deeply entrenched organised criminal groups that cause both economic and social damage. Overcoming, or at least limiting, their harmful effects is a societally beneficial objective, which renders its dynamics understanding an objective of both scientific and political interests. We propose an agent-based simulation model aimed at understanding how independent and combined effects of legal and social norm-based processes help to counter mafias. Our results show that legal processes are effective in directly countering mafias by reducing their activities and changing the behaviour of the rest of population, yet they are not able to change people’s mind-set that renders the change fragile. When combined with social norm-based processes, however, people’s mind-set shifts towards a culture of legality rendering the observed behaviour resilient to change.

SummaryThe ratio of males to females in a population is known to influence the behaviour, life histories and demography of animals. A recent experimental study finds that sex ratio also affects human economic behaviour, and in a manner consistent with evolutionary theory.