Bibliographic record
Abstract
Résumé Forme la plus controversée de l’ affirmative action , la discrimination positive octroie aux membres de groupes ayant été soumis dans le passé à un régime juridique discriminatoire d’ampleur variable un traitement préférentiel dans la répartition de certains biens disponibles en quantité limitée (emplois, marchés publics, offres d’admission dans des établissements d’enseignement supérieur à caractère sélectif). Si le bilan provisoire que l’on peut tirer de cette politique est contrasté – très mitigé dans le cas des marchés publics mais assez nettement positif concernant les universités –, force est de constater que le démantèlement partiel des programmes en question intervenu dans certains États depuis la seconde moitié des années 1990 a immédiatement donné lieu à une multiplication de mesures à vocation substitutive relevant d’une discrimination positive indirecte. En dépit des apparences, l’élimination de l’ensemble des politiques redistributives prenant en compte, de manière plus ou moins manifeste, le facteur ethno-racial n’est donc pas à l’ordre du jour.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.012 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 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".