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Observational analysis explores how statistical norms influence perceptions of blame and praise, suggesting notable differences in frequency impact.
For many types of behaviors, whether a specific instance of that behavior is blame- or praiseworthy depends on how much of the behavior is done or how people go about doing it. For instance, for a behavior such as "replying to an email in x days," whether a specific reply is perceived as blameworthy or praiseworthy will depend on how many days have elapsed before the reply. Such behaviors lie on a continuum in which part of the continuum is praiseworthy (replying quickly) and another part of the continuum is blameworthy (replying late). In the current paper, we investigate how judgments of blame and praise on such behaviors relate to people's perceptions of the statistical norms surrounding that behavior (i.e., how quickly people usually reply). We find that people do not base judgments of blame and praise on a comparison to the statistically average quantity. Instead, judgments of blame and praise are related to whether the behavior is perceived as frequent or infrequent. Notably, frequency showed an asymmetric relationship with moral judgments: higher frequency was strongly associated with reduced blame but showed a much weaker association with reduced praise.
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Bostyn et al. (2025) studied this question.
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