An exploration of gender, interlocking directorates, and corporate performance
Bibliographic record
Abstract
Purpose The purpose of this study is to explore the impact that women who sit on boards of directors, as well as women that are part of an interlocking directorate, have on corporate performance. The investigation is placed within the literature on human capital theory and resource dependency as an argument for gender diversity and boards of directors. Design/methodology/approach A director data set for over 32,000 firms based in the USA, composed of 6,218 women and 54,932 men, is utilized. From this, regression and network analysis were utilized. Findings It is found that female directors’ participation in interlocking directorates translates into greater corporate performance when compared to simply examining female representation on boards of directors. Additionally, women involved in interlocks translated into greater corporate performance when compared to men. These results support the resource dependency approach. Practical/implications Results of this study suggest that when considering female directors, corporate performance is enhanced when female directors already sit on the boards of other firms. Originality/value This study highlights external network connections to differentiate between human capital theory and resource dependency as an argument for gender diversity and boards of directors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".