Governance, Ownership Structure, and Financial Leverage: The Role of Board Gender Diversity in UK Firms
Bibliographic record
Abstract
This paper aims to investigate the relationship between governance structure, ownership structure, and financial leverage of corporations in the UK, with a special emphasis on the boardroom gender diversity. The study sample includes 484 UK firms from the FTSE All-Share Index for the period (2015–2023), with 4356 firm-year observations. The results show that CEO duality, gender diversity, managerial ownership, institutional ownership, and government shareholding are all positively associated with financial leverage, thus confirming the importance of these governance and ownership characteristics in determining capital structure policies. On the other hand, board size and the proportion of non-executive directors are not found to have a significant impact on financial leverage, which points to some room for improvement in UK board practices. In this regard, the study contributes to the governance-sustainability-finance nexus discussion by focusing on these dimensions in the UK corporate sector. As such, the findings of this study are important in providing policy recommendations for policymakers and corporate leaders and contribute to the ongoing wave of global corporate governance reforms and practical insights into enhancing governance frameworks at the firm level.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".