Accroître la nomination des femmes arbitres au sein des tribunaux arbitraux sportifs : la diversité au-delà du Tribunal arbitral du sport
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Le manque de diversité en arbitrage est fréquemment dénoncé. Une de ses manifestations est le faible taux de nominations de femmes sur des tribunaux arbitraux. Dans le domaine du sport, la situation est pire encore qu’en arbitrage commercial ou d’investissement. Le Tribunal arbitral du sport se classe ainsi bon dernier dans les statistiques de nominations de femmes arbitres, ainsi que dans les initiatives pour pallier ces problèmes. Cet article examine le rôle de ce dernier et des fédérations sportives, ainsi que les avenues qui pourraient les inspirer pour atteindre une meilleure représentativité au sein des tribunaux arbitraux.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it