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Record W3212455968 · doi:10.1177/09567976211031208

Harsh but Expedient: Dominant Leaders Increase Group Cooperation via Threat of Punishment

2021· article· en· W3212455968 on OpenAlexafffund
Fan Xuan Chen, Xinyu Zhang, Lasse Laustsen, Joey T. Cheng

Bibliographic record

VenuePsychological Science · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicEvolutionary Game Theory and Cooperation
Canadian institutionsYork University
FundersSocial Sciences and Humanities Research Council of CanadaYork University
KeywordsPsychologyPunishment (psychology)Group (periodic table)Social psychologyCriminologyChemistry

Abstract

fetched live from OpenAlex

Dominant leadership is, surprisingly, on the rise globally. Previous studies have found that intergroup conflict increases followers’ support for dominant leaders, but identifying the potential benefits that such leaders can supply is crucial to explaining their rise. We took a behavioral-economics approach in Study 1 ( N = 288 adults), finding that cooperation among followers increases under leaders with a dominant reputation. This pattern held regardless of whether dominant leaders were assigned to groups, elected through a bidding process, or leading under intergroup competition. Moreover, Studies 2a to 2e ( N = 1,022 adults) show that impressions of leader dominance evoked by personality profiles, authoritarian attitudes, or physical formidability similarly increase follower cooperation. We found a weaker but nonsignificant trend when dominance was cued by facial masculinity and no evidence when dominance was cued by aggressive disposition in a decision game. These findings highlight the unexpected benefits that dominant leaders can bestow on group cooperation through threat of punishment.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.346
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.045
GPT teacher head0.369
Teacher spread0.324 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations29
Published2021
Admission routes2
Has abstractyes

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