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Moral cleansing as hypocrisy: When private acts of charity make you feel better than you deserve.
Open accessAbstract
What counts as hypocrisy? Current theorizing emphasizes that people see hypocrisy when an individual sends them "false signals" about his or her morality (Jordan, Sommers, Bloom, & Rand, 2017); indeed, the canonical hypocrite acts more virtuously in public than in private. An alternative theory posits that people see hypocrisy when an individual enjoys "undeserved moral benefits," such as feeling more virtuous than his or her behavior merits, even when the individual has not sent false signals to others (Effron, O'Connor, Leroy, & Lucas, 2018). This theory predicts that acting less virtuously in public than in private can seem hypocritical by indicating that individuals have used good deeds to feel less guilty about their public sins than they should. Seven experiments (N = 3,468 representing 64 nationalities) supported this prediction. Participants read about a worker in a "sin industry" who secretly performed good deeds. When the individual's public work (e.g., selling tobacco) was inconsistent with, versus unrelated to, the good deeds (e.g., anonymous donations to an antismoking cause vs. an antiobesity cause), participants perceived him as more hypocritical, which in turn predicted less praise for his good deeds. Participants also inferred that the individual was using the inconsistent good deeds to cleanse his conscience for his public work, and such moral cleansing appeared hypocritical when it successfully alleviated his guilt. These results broaden and deepen understanding about how lay people conceptualize hypocrisy. Hypocrisy does not require appearing more virtuous than you are; it suffices to feel more virtuous than you deserve. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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Metadata
- Authors
- O'Connor, K., Effron, D. A., & Lucas, B. J.
- Affiliations
- Cornell University (US)
- Corresponding author
- O'Connor, Kieran
- Venue
- Journal of Personality and Social Psychology
- Published
- 2020-09
- Volume
- 119
- Issue
- 3
- Pages
- 540-559
- ISSN
- 0022-3514 (ISSN-L)
- 1939-1315
- OpenAlex
- W3019944746
- Semantic Scholar
- f76d5f29562a19cb162f7c8a389fd04c21177883
- Cited by
- 65
- References
- 115
- Citations by year
- 2026: 11 · 2025: 13 · 2024: 9 · 2023: 16 · 2022: 8 · 2021: 6 · 2020: 2
- FWCI
- 3.82
- Type
- journal article
- Language
- en
- Open access
- Locations
- Journal of Personality and Social Psychology (publishedVersion)
- PubMed (publishedVersion)
- London Business School Research Online (London Business School) (submittedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Psychology of Moral and Emotional Judgment
- Social Sciences › Psychology › Social Psychology › Emotions and Moral Behavior
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Ethics in Business and Education
- Keywords
- hypocrisy, moral cleansing, moral self-perception, guilt, false signals, moral self-presentation
- MeSH terms
- Adult, Altruism, Conscience, Female, Guilt, Humans, Deception, Male, Self Concept
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.