Mettre les pendules à l'heure : Preuve scientifique, preuve statistique, preuve culturelle
Bibliographic record
Abstract
Ce texte a été suscité à la lecture de divers écrits publiés dans les médias à la suite des débats politiques ayant entourés l'adoption du projet de loi 23 adopté le 7 décembre 2023 par l'Assemblée nationale du Québec. Il traite de 10 questions : 1° L'origine de la recherche en pédagogie, 2° la distinction entre les preuves scientifiques et statistiques, 3° la possibilité de la recherche expérimentale en éducation, 4° la perception dictatoriale des données probantes, 5° les autres forme de recherches, 6° Les dites preuves culturelles, 7° de l'évidentialité et des preuves culturelles et basées sur la pratique, 8° le rôle des autres formes de recherche, 9° les études de cas et les études pilotes et 10° l'ambiguïté des discours en éducation entre idéologie et science, entre continuité et course à l'innovation. Il complète un premier texte de Gauthier, C., Bissonnette, S. et J.M. Van der Maren : La pertinence de l'utilisation des données probantes en éducation èà la lumière des rapports théorie-pratique. Accessible sur https://r-libre.teluq.ca/3064/.
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 | 0.022 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.012 | 0.031 |
| Scholarly communication | 0.018 | 0.015 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".