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Record W4408350552 · doi:10.1016/j.ribaf.2025.102867

How do women directors ensure corporate ethics? The role of board tenure

2025· article· en· W4408350552 on OpenAlexafffund
Nancy D. Ursel, Ligang Zhong

Bibliographic record

VenueResearch in International Business and Finance · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsUniversity of Windsor
FundersSocial Sciences and Humanities Research CouncilSocial Sciences and Humanities Research Council of Canada
KeywordsBusinessAccountingCorporate governanceBusiness ethicsPublic relationsFinancePolitical science

Abstract

fetched live from OpenAlex

Women board members have been shown to reduce corporate misconduct. We ask how they accomplish this given that their numbers are small, their voices often go unheard, and they tend to be on committees that have been considered less important. Using social identity theory and the theory of gendered expectations, we hypothesize that long tenure on the board is the characteristic that allows a woman director’s voice to be heard. We test our hypothesis by looking at women directors’ power to reduce stock option backdating. Our hypothesis regarding long tenure is supported. Other sources of power such as critical mass, prestige and ownership power are not significantly related to reduced corporate misconduct. We use logit regression and perform several robustness checks, including instrumental variable techniques to deal with possible endogeneity. We discuss the implications of our findings for management practice and board structure. • Long tenure on the board allows women directors’ voices to be heard • Long-tenured women directors reduce option backdating misconduct • Other forms of power do not help women directors reduce corporate misconduct

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.587
Threshold uncertainty score0.692

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.183
GPT teacher head0.383
Teacher spread0.199 · 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 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

Citations0
Published2025
Admission routes2
Has abstractyes

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