Women Managers: Enormous Deficit in Large Companies and Employer's Associations
Bibliographic record
Abstract
Across Europe, there are much fewer women than men employed in executive positions. On European average, only 10% of the members of the highest decision-making bodies in the top 50 publicly quoted companies are women. However, the situation varies substantially from country to country. The European countries with the highest shares of women managers are Slovenia and Latvia, at 22% each, while the country with the worst record is Italy, at 2%. Germany, with a 10% share of women managers, is in the middle of the ranking order. However, the picture in Germany becomes less favourable when the figures for enterprises and associations are examined separately. For example, women occupy only 1% of the seats on the boards of management and 8% of the seats on the supervisory boards of Germany's 87 largest 'old economy' joint-stock companies. The situation is more favourable in the workers' representative bodies and the professional associations, where women account for between one fifth and one quarter of the executives - a figure that is still far removed from parity, however. Even under the broader definition of specialist and managerial staff in all areas of white-collar and public-service employment, the share of women is still less than one third, although women account for 45% of total employment in these areas. The German business sector's agreement of 2001 with the German government to commit itself to voluntarily promoting equal opportunity for women and men in the private sector has had very little impact to date at managerial level. Substantial effort is still required if this situation is to improve.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".