RT Article
T1 Recruitment into Organized Crime: An Agent-Based Approach Testing the Impact of Different Policies
JF Journal of quantitative criminology
VO 38
IS 1
SP 197
OP 237
A1 Calderoni, Francesco
A2 Campedelli, Gian Maria
A2 Szekely, Aron
A2 Paolucci, Mario
A2 Andrighetto, Giulia
LA English
YR 2022
UL https://krimdok.uni-tuebingen.de/Record/1884548784
AB 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.
K1 Generalized estimating equations
K1 Agent-based model
K1 Multiplex networks
K1 Involvement
K1 Recruitment
K1 Embeddedness
K1 Criminal networks
K1 Organized Crime
DO 10.1007/s10940-020-09489-z