Le « système de dépôt et de communication de renseignements en éducation » prévu dans la loi 23 : vers une infrastructure de gestion pédagogique ?
Bibliographic record
Abstract
Adoptée le 7 décembre 2023, la loi 23 prévoit un « système de dépôt et de communication de renseignements en éducation », dont les finalités, les usages et les implications ont été peu débattus. Quel sens lui donner ? Cet essai porte sur le rôle que pourrait jouer le système de dépôt et de communication de renseignements sur la base de tendances politiques et techniques documentées scientifiquement au Québec et à l’international. Nous rapprochons le système de dépôt et de communication de renseignements d’un certain type d’usage des données scolaires : celui de la responsabilisation. Cet usage nous semble discutable du fait qu’il consiste à gérer la pédagogie par les chiffres, une finalité qui soulève plusieurs enjeux.
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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 | 0.032 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.016 | 0.013 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.020 | 0.006 |
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".