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Record W4388501586 · doi:10.1002/ejsp.3009

Mind the gap: Wise reasoning attenuates gender pay gap scepticism in men

2023· article· en· W4388501586 on OpenAlexafffund
Justin P. Brienza, Anna Dorfman, D. Ramona Bobocel

Bibliographic record

VenueEuropean Journal of Social Psychology · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsUniversity of Waterloo
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of Queensland
KeywordsSkepticismPsychologyBiology and political orientationPerceptionSocial psychologyGender gapHumilityPerspectivismMotivated reasoningPsychological interventionPoliticsEpistemologyPolitical scienceDemographic economics

Abstract

fetched live from OpenAlex

Abstract We draw from theory on motivated reasoning to suggest that men would be more prone toward gender pay gap scepticism (PGS) than women because doing so maintains a valued but illusory belief that society is currently fair. Integrating theory on wisdom and wise reasoning —a self‐transcendent thinking process composed of intellectual humility, contextualism, perspectivism and dialecticism—we also hypothesised that men who engaged in stronger (vs. weaker) wise reasoning about the pay gap would be less prone toward PGS. Two pre‐registered studies ( N = 651) supported the predictions: generally, men were more prone toward gender PGS than women, while wise reasoning tended to attenuate scepticism in men. The patterns of effects remained stable when controlling for income, education, political orientation, and perceptions of the effects of COVID‐19 on women's economic and psychological well‐being. Our studies pave the way for interventions that alter how people reason about inequities such as the gender pay gap in an effort to create fairer workplaces and societies.

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)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.603
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.112
GPT teacher head0.400
Teacher spread0.287 · 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 designNot applicable
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

Citations6
Published2023
Admission routes2
Has abstractyes

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