A computational model of strategic punishment in divided societies
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A computational model of strategic punishment in divided societies

Creative Commons 'BY' version 4.0 license
Abstract

In divided societies, authorities often use punishment to establish shared norms while trying to maintain or signal their legitimacy. When facing a polarized audience, these goals may often be at odds. We extend the Rational Communicative Social Action (RCSA) framework (Radkani et al., 2022) to formally model an authority's strategic decision-making when using public punitive actions to pursue these goals. We distinguish between a communicative authority who aims to shape the audience's moral beliefs, and a reputation-aware authority who optimizes the audience's assessment of their own character. By simulating these agents against polarized audiences, we characterized the tradeoffs and dynamics of strategic punishment when facing diverse audiences with various forms and levels of polarization, which serves to generate systematic predictions for future experiments.