D4.3 Policy Brief on equal opportunities in employment for men and women
Bibliographic record
Abstract
In all European Union (EU) Member States, a larger percentage of men are employed compared to women (European Commission, 2025). According to the latest EU employment and social developments report (2025), nearly one quarter of women remain outside the labour market. Yet, empowering women and ensuring their full participation across all sectors of the labour market can significantly boost the EU’s productivity and economic growth (EIGE, 2025). This persistent gender imbalance highlights the need for a deeper understanding of the barriers that prevent women from fully participating in the labour market.In March 2025, the EU Roadmap for Women’s Rights was adopted, setting out a long-term vision for fully achieving equal opportunities for women in Europe. Moreover, the European Pillar of Social Rights Action Plan aims to increase overall employment in the EU by 2030, including to at least halve the gender employment gap compared to 2019. In addition, with the new Gender Equality Strategy 2026-2030, the European Commission aims to outline concrete measures to be taken to further advance gender equality in Europe.
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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 | 0.023 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.016 | 0.012 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.085 | 0.029 |
| Insufficient payload (model declined to judge) | 0.038 | 0.019 |
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".