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Cited by 511

The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.

With a Clean Conscience: Cleanliness Reduces the Severity of Moral Judgments

Open access
Schnall, Simone, Benton, Jennifer, Harvey, Sophie·2008·Psychological Science

Abstract

Theories of moral judgment have long emphasized reasoning and conscious thought while downplaying the role of intuitive and contextual influences. However, recent research has demonstrated that incidental feelings of disgust can influence moral judgments and make them more severe. This study involved two experiments demonstrating that the reverse effect can occur when the notion of physical purity is made salient, thus making moral judgments less severe. After having the cognitive concept of cleanliness activated (Experiment 1) or after physically cleansing themselves after experiencing disgust (Experiment 2), participants found certain moral actions to be less wrong than did participants who had not been exposed to a cleanliness manipulation. The findings support the idea that moral judgment can be driven by intuitive processes, rather than deliberate reasoning. One of those intuitions appears to be physical purity, because it has a strong connection to moral purity.

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Crossref · 10.1111/j.1467-9280.2008.02227.x

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Metadata

Authors
Schnall, S., Benton, J., & Harvey, S.
Venue
Psychological Science
Published
2008-12
Volume
19
Issue
12
Pages
1219-1222
ISSN
  • 0956-7976 (ISSN-L)
  • 1467-9280
OpenAlex
W2146430341
Cited by
511
References
17
FWCI
9.09
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: With a Clean Conscience: Cleanliness Reduces the Severity of Moral Judgments. https://app.cochat.ai/papers/10.1111/j.1467-9280.2008.02227.x
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Schnall, S., Benton, J., & Harvey, S. (2008). With a Clean Conscience: Cleanliness Reduces the Severity of Moral Judgments. Psychological Science. https://doi.org/10.1111/j.1467-9280.2008.02227.x

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.