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Record W1921219746 · doi:10.1111/caje.12123

Leadership and gender in groups: An experiment

2015· article· en· W1921219746 on OpenAlexvenueno aff
Philip J. Grossman, Mana Komai, James E. Jensen

Bibliographic record

VenueCanadian Journal of Economics/Revue canadienne d économique · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicExperimental Behavioral Economics Studies
Canadian institutionsnot available
FundersAustralian Research CouncilNational Science Foundation
KeywordsLeadership styleSocial psychologyPsychologyLegitimacyPosition (finance)Style (visual arts)Transactional leadershipLeadershipTransformational leadershipOutcome (game theory)Shared leadershipPolitical sciencePublic relationsBusinessLawEconomics

Abstract

fetched live from OpenAlex

Abstract We conduct a laboratory experiment to study gender differences in leadership. We strip the concept of leadership down to its most basic elements. Questions of style and evaluations of a leader based on style of leadership adopted are made irrelevant. Our leader is an average player who is distinguished merely by occupying the leadership position. Legitimacy is conferred on the leader by the special information possessed. Followers voluntarily choose whether or not to follow the better‐informed leader. The effectiveness of the leader is reduced to two simple factors: is the leader willing or not to voluntarily place him/herself in a vulnerable position to achieve an outcome beneficial to both the leader and his/her followers? Do followers trust their leaders to make the right choice? We provide experimental evidence that female leaders and followers are more cooperative than the males in most circumstances. Female leaders show a hesitation to lead in mixed‐gender environments with gender signalling in circumstances where followers' refusal to follow can significantly hurt them. The behaviour of the followers is the same toward the leaders regardless of their gender.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0130.001

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 head0.494
GPT teacher head0.285
Teacher spread0.209 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
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

Citations37
Published2015
Admission routes1
Has abstractyes

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