La double vraisemblance au fondement de la collaboration de recherche : retour sur la démarche de coconstruction d’un projet entrepreneurial à l’école primaire
Bibliographic record
Abstract
Nous proposons dans cet article une analyse de la collaboration entre une enseignante et un chercheur dans le cadre d’une recherche doctorale visant à documenter l’apprentissage à s’entreprendre d’élèves du primaire à l’appui d’un projet de magasin scolaire. Le concept de « double vraisemblance » est convoqué en tant qu’il permet de jeter un regard analytique éclairant sur la démarche de collaboration de recherche. Trois moments de négociation des points de vue des partenaires sont plus spécifiquement analysés comme révélateurs des enjeux à la fois respectifs et communs qui les mobilisent dans la construction de la double vraisemblance du projet de magasin, au bénéfice de l’apprentissage à s’entreprendre des élèves.
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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 | 0.028 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.010 | 0.025 |
| Scholarly communication | 0.015 | 0.011 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".