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Record W4413298521 · doi:10.1080/1351847x.2025.2541776

Does female bank leadership affect firm credit? <sup>+</sup>

2025· article· en· W4413298521 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEuropean Journal of Finance · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsAffect (linguistics)BusinessFinancial systemMonetary economicsFinanceEconomicsPsychology

Abstract

fetched live from OpenAlex

This study examines how female bank leadership influences firms’ bank debt. We combine bank-level and firm-level data to construct a sample of about 101,000 firms from eleven European countries. Overall, our results indicate that female and male bank leaders allocate credit differently. We find that female bank leadership globally reduces firms’ bank debt. This effect varies with the maturity of bank debt, as female bank leadership contributes to lower long-term bank debt but higher short-term bank debt. We also find that female bank leadership is associated with lower firms’ bank debt only for male-led companies, and that the effect on firm bank debt becomes significantly positive for larger firms. Although greater female bank leadership may reduce access to credit of firms overall, female bank leaders may still implement less risky lending policies and reduce the gender gap in access to credit for female-led firms.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.124
Threshold uncertainty score0.650

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.033
GPT teacher head0.220
Teacher spread0.187 · 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