Human Rights Enforcement Agencies and the Protection of Older Workers Against Discrimination
Bibliographic record
Abstract
The article provides insight into the way a human rights enforcement agency, the Quebec Human Rights Commission, implements legal dispositions prohibiting age discrimination in employment. Drawing on data from claims filed before the Commission, the article establishes a quantitative profile of cases and examines the factors that are involved in the decisions made by the Commission. It is argued that (1) the Commission's approach in investigating age discrimination cases and (2) the burden of proof put on respondents are main contributing factors to a very limited number of cases being validated. However, despite apparent shortcomings, the Commission still fulfills an important role in defending and promoting older workers' rights. Its overall impact can be assessed only in connection with other social and employment policies geared at older workers. In conclusion, some recommendations to improve the functioning of the Commission are made.
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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 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.012 | 0.012 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".