Breaking the Cycle: An Agent-Based Model on the Efficacy of Inclusivity Norm Interventions to Reduce Affective Polarization within an Ethnic Majority Group.

This study examines whether and how a social network norm intervention that promotes inclusive attitudes towards ethnic minority groups can induce lower levels of steady-state affective polarization across generations of an ethnic majority group in a society with high initial levels of affective polarization. We investigate the efficacy of such an intervention if it is targeted at four types of socializing agents in the ethnic majority group (parents, peers, teachers, and the media) in empirically calibrated social networks with different types of structures (i.e., the relationships between all actors and agents in the network) and compositions (i.e., the initial distribution of attitudes across agents and actors). Based on empirical work, we specify a range of likelihoods for the intervention to enact a change of a particular magnitude in the attitudes of a socializing agent. Based on social learning theory, we assume that actors observe and learn the attitudes of socializing agents in their social environment, represented as a social network. Again, based on empirical work, we assume a particular magnitude of transmission between each agent and actor in various life course stages. From a social identity perspective, we argue that the likelihood for actors to adopt more positive attitudes towards ethnic out-groups from an agent first depends on how representative the agent is of the collective in-group identity. From a complex contagion perspective, we further argue that this likelihood depends on how many, to what degree, and how consistently the socializing agents in the actors’ social network adopt inclusivity norms. Based on this theoretical framework, we generate hypotheses that are evaluated with a stochastic actor-oriented model, which simulates the evolution of ethnic majority group attitudes towards ethnic minorities across generations for each of the conditions in our design.