The impact of female directors on firm risk: A study in the context of G6 countries
Bibliographic record
Abstract
he main objective of this study is to assess the impact of female directors on firm risk in the G6 countries (all G7 countries except Italy, since data for Italy are not available). A total of 4617 firm-year observations were collected from six countries: the United States, Japan, Germany, the United Kingdom, France, and Canada. The firm risk measures (risk1 and risk2) are calculated as the ratio of a firm profitability to volatility of profitability. These risk measures capture the risk-seeking behavior of the firm. These ratios are a comprehensive measure of risk-seeking behavior since they capture the decisions made by the incumbent management related to the firm’s operations. The results show that the presence of female directors beyond a threshold point reduces firm risk in the total dataset as well as in individual countries. Interestingly, Europe as a continent and all European countries individually have the highest impact of the presence of female directors above the threshold. In the case of Japan, the presence of female directors has the least influence on firm risk
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".