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The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

Retracted: Evil Genius? How Dishonesty Can Lead to Greater Creativity

Gino, Francesca, Wiltermuth, Scott S.·2014·Psychological Science

Abstract

We propose that dishonest and creative behavior have something in common: They both involve breaking rules. Because of this shared feature, creativity may lead to dishonesty (as shown in prior work), and dishonesty may lead to creativity (the hypothesis we tested in this research). In five experiments, participants had the opportunity to behave dishonestly by overreporting their performance on various tasks. They then completed one or more tasks designed to measure creativity. Those who cheated were subsequently more creative than noncheaters, even when we accounted for individual differences in their creative ability (Experiment 1). Using random assignment, we confirmed that acting dishonestly leads to greater creativity in subsequent tasks (Experiments 2 and 3). The link between dishonesty and creativity is explained by a heightened feeling of being unconstrained by rules, as indicated by both mediation (Experiment 4) and moderation (Experiment 5).

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Crossref · 10.1177/0956797614520714This paper is marked retracted.

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Metadata

Authors
Gino, F., & Wiltermuth, S. S.
Venue
Psychological Science
Published
2014-02-18
Volume
25
Issue
4
Pages
973-981
ISSN
  • 0956-7976 (ISSN-L)
  • 1467-9280
OpenAlex
W2106303383
Cited by
185
References
5
FWCI
20.85
Type
journal article
Language
en
Status
Retracted
Open access
closed

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CoChat. (2026). Citation check: Retracted: Evil Genius? How Dishonesty Can Lead to Greater Creativity. https://app.cochat.ai/papers/10.1177/0956797614520714
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Gino, F., & Wiltermuth, S. S. (2014). Retracted: Evil Genius? How Dishonesty Can Lead to Greater Creativity. Psychological Science. https://doi.org/10.1177/0956797614520714

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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.