The Effect of Board Gender Diversity and Environmental Responsibility on Innovation: Evidence from the Top-Patenting Firms
Bibliographic record
Abstract
Today, firms face joint pressures to increase the representation of women at the highest levels of their organizations, and to be more environmentally responsible. Still, the impact of these movements on firm performance is less clear. Through the lens of the Attraction-Selection-Attrition (ASA) Cycle, this study looks at the impact of Board Gender Diversity (BGD) and Environmental Responsibility on Innovative Output as measured by patents. Using a longitudinal sample of the top-patenting firms at the United States Patent and Trademark Office, we find that both BGD and Environmental Responsibility lead to higher levels of Innovative Output, and BGD positively moderates the relationship between Environmental Responsibility and Innovative Output. This paper contributes to existing literature by highlighting the need to consider BGD and Environmental Responsibility at the same time when considering their implications on firm performance. We also expand the scope of the ASA Cycle to include overall firm performance with respect to innovation.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".