Acceso usuarios
Zachary J. Davis, Kelsey R. Allen, Max Kleiman Weiner, Julian Jara-Ettinger, Tobias Gerstenberg
People have a remarkable ability to infer the hidden causes of things. From physical evidence, such as muddy footprints on the floor, we can figure out what happened and who did it. Here, we investigate another source of evidence: social evaluations. Social evaluations, such as praise or blame, are commonplace in everyday conversations. While such evaluations do not fully reveal what happened, they provide valuable clues. Across three experiments, we present situations where a person was praised or blamed, and participants’ task is to use that information to figure out what happened. In Experiment 1, we find that people draw systematic inferences from social evaluations about situational factors, a person’s actions, capabilities, and social roles. In Experiments 2 and 3, we develop computational models that generate praise and blame judgments by considering what causal role a person’s action played, and what action they should have taken. Inverting these generative models of praise and blame via Bayesian inference yields accurate predictions about what inferences participants draw based on social evaluations. (PsycInfo Database Record (c) 2025 APA, all rights reserved)
