Microprogramme de deuxième cycle en éducation (2-812-6-0),avec spécialisation en intégration pédagogique des technologies de l’information et de la communication, Programme spécialement adapté pour le Conseil en Éducation des Premières Nations (CEPN), http://cepn.scedu.umontreal.ca
Bibliographic record
Abstract
I Présentation de l’Université de Montréal, p.3; II Présentation de la Faculté des sciences de l’éducation, p.4; III Présentation du Conseil en Éducation des Premières Nations, p.5; IV Qu'est-ce qu'un microprogramme à l’Université de Montréal ? p.6; V Objectifs du microprogramme en intégration pédagogique des TIC, p.7; VI Postulats du microprogramme en intégration pédagogique des TIC, p. 8; VII Admission et inscription, p.9; VIII Ouvertures possibles du microprogramme en intégration pédagogique des TIC, p.10; IX Équipe professorale, p.10; X Formule pédagogique, p.11; XI Encadrement pédagogique, p.12; XII Évaluation continue de la formation, p. 14; XIII Structure et durée du programme, p.15; XIV Structure du microprogramme proposé, p.17; XV Cours du programme, p.18; Annexe I Formulaire d’admission;Annexe II Conditions d’efficacité des FOAD; Annexe III Détails sur la visioconférence.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.399 | 0.109 |
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".