Do Female Top Managers Help Women to Advance? A Panel Study Using EEO-1 Records
Bibliographic record
Abstract
The goal of this study is to examine whether women in the highest levels of firms’ management ranks help to reduce barriers to women’s advancement in the workplace. Using a panel of more than twenty thousand firms during 1990 to 2003 from the U.S. Equal Employment Opportunity Commission, the authors explore the influence of women in top management on subsequent female representation in lower-level managerial positions in U.S. firms. Key findings show that an increase in the share of female top managers is associated with subsequent increases in the share of women in midlevel management positions within firms, and this result is robust to controlling for firm size, workforce composition, federal contractor status, firm fixed effects, year fixed effects, and industry-specific trends. The authors also find that the positive influence of women in top leadership positions on managerial gender diversity diminishes over time, suggesting that women at the top play a positive but transitory role in women’s career advancement.
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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 | 0.002 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".