Cadre de référence pour l’apprentissage expérientiel: Guide synthèse
Bibliographic record
Abstract
Le Cadre d'apprentissage expérientiel (AE) de l'Université d'Ottawa est un outil à la fois pratique et stratégique conçu pour appuyer le développement de programmes, la conception de cours et la reconnaissance d'activités d'AE de haute qualité. Développé à l'origine dans le cadre de la création du Régime d'apprentissage expérientiel approfondi (RAEA), un parcours de 30 crédits de premier cycle de cours labellisés AE, ce cadre a depuis évolué pour devenir un guide institutionnel global visant à favoriser la cohérence, la qualité et la visibilité de l'offre en AE. Alors que de nouvelles formes d'AE sont développées sur le campus, le Cadre demeure un outil adaptatif qui continuera d'évoluer selon les besoins et les nouvelles opportunités.
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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 | 0.019 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.023 | 0.004 |
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".