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Record W4408350220 · doi:10.1016/j.jesp.2025.104746

The plurality effect: People are more dishonest toward group than individual targets

2025· article· en· W4408350220 on OpenAlexafffund
Hsuan‐Che Huang, Ruodan Shao, Ann E. Tenbrunsel, Kristina A. Diekmann, Daniel P. Skarlicki

Bibliographic record

VenueJournal of Experimental Social Psychology · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsYork UniversityUniversity of British Columbia
FundersSocial Sciences and Humanities Research CouncilSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologySocial psychologyGroup (periodic table)Chemistry

Abstract

fetched live from OpenAlex

Prior research on the relationship between group versus individual targets and unethical behavior directed toward those targets is incomplete. Extending this line of research, the present paper examines whether individuals engage in more dishonest behaviors when interacting with a group (vs. an individual). Across six experiments and three supplemental studies ( N = 2376), we found that individuals demonstrated more dishonesty toward groups as opposed to individual targets, which we label the plurality effect . This effect was observed across a variety of situations (both low-stakes and high-stakes contexts with real monetary payouts), including when providing advice to others with an incentive to be dishonest, in employment interviews, and in negotiations. Mediation tests revealed that participants experienced lower moral concern when the target was a group versus an individual, and this finding held after testing for alternative explanations. Group membership and collectivism jointly moderated the effect, such that the plurality effect was stronger for targets who are members of the decision makers outgroup (vs. ingroup) among decision makers with high (vs. low) collectivistic values.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.556
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.030
GPT teacher head0.417
Teacher spread0.387 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2025
Admission routes2
Has abstractyes

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