Framing Institutional Corruption: A Behavioral Simulation of Moral Judgment and Accountability Narratives

This paper examines how institutional narratives of corruption shape moral judgment and trust. Using a sequential, exploratory mixed-methods design grounded in pragmatic epistemology, we first analyze public texts from three European cases (Airbus, FIFA, and Sarkozy) to identify four recurring frames: reformism, deferral, externalization, and minimization. We then translate these frames into controlled manipulations in a transparent Python simulation featuring two evaluator profiles: a rule-based, justice-motive agent and a narrative-sensitive, heuristic agent parameterized from behavioral-ethics theory. With underlying events held constant and only the narrative tone altered, Monte-Carlo summaries show a consistent ordering: punitive frames depress trust and heighten organizational blame, reformist frames have the opposite effect, and neutral frames fall in between. Effects are larger for the heuristic agent and minimal for the rule-based agent, consistent with the hypotheses on moral-disengagement cues, framing consequences, and dual-process moderation. Results are interpreted descriptively, not inferentially, and all materials are publicly available for replication. Theoretically, the study extends moral disengagement from an intrapsychic to a communicative mechanism, showing how rhetoric transmits ethical leniency to audiences. It proposes a four-frame audit tool that regulators, boards, and journalists can use to detect “narrative laundering” in accountability statements. Limitations include stylized agents, a European focus, and text-only stimuli, motivating human-participant and cross-cultural validation.