Essai d'un modèle naturaliste dans l'évaluation du certificat de relations industrielles (Université de Montréal)
Bibliographic record
Abstract
L'évaluation du programme de relations industrielles 1 à la F.E.P. (Faculté de l'Éducation Permanente) nous offre l'occasion d'appliquer le modèle conjoncturel*, qui a été introduit par Stake (1975) ainsi que Guba et Lincoln (1981a) dans la littérature concernant les modèles d'évaluation de programme d'études. L'utilisation de cette approche nous a permis de dresser un portrait de la situation, d'établir un consensus au niveau des différents groupes impliqués concernant les problèmes auxquels se confrontent le certificat et de formuler des recommandations appropriées. Cette expérience nous a aussi permis d'identifier les avantages et les limites reliés à l'application du modèle conjoncturel ainsi que de les confronter avec le point de vue de d'autres utilisateurs.
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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 | 0.021 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 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".