La triade science, technologie et environnement : nouveaux enjeux théoriques curriculaires et pédagogiques
Bibliographic record
Abstract
S’inscrivant dans une mouvance mondiale en éducation scientifique, la réforme québécoise du curriculum de sciences implique un virage théorique et pratique important. L’apprentissage des sciences ne sera plus basé sur une logique monodisciplinaire traditionnelle, mais plutôt sur un questionnement dirigé vers des objets, des phénomènes, des contextes, etc. Cette nouvelle approche implique donc le croisement de divers savoirs scientifiques. Celle-ci implique également des croisements avec de « nouveaux venus » dans les programmes scientifiques scolaires : l’éducation technologique et l’éducation relative à l’environnement. À travers cet écrit, nous explorerons les principaux enjeux théoriques et pratiques du croisement des champs d’intervention de l’éducation relative aux sciences, de l’éducation relative à la technologie et de l’éducation relative à l’environnement.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.037 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".