Bibliographic record
Abstract
The use of affirmative action to increase women's representation in employment is recognized under European Community law. The European Court of Justice has identified affirmative action permissible under EC law and what constitutes reverse discrimination, deemed incompatible with the equal treatment principle. Despite these developments, gendered occupational segregation — vertical and horizontal — persists in all member states as evidenced by enduring pay gaps. It is widely argued that we now need national measures which take advantage of the appropriate framework and requisite political will which exists at the European level. Faced with a similar challenge, the Canadian government passed the Employment Equity Act 1986 which places an obligation on federal employers to implement employment equity (affirmative action) by proactive means. Although subject to some criticism, there have been some improvements in women's representation since its introduction. This article assesses what lessons might be learned from Canada's experience.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.039 | 0.013 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 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".