Analyse transversale des projets de recherches participatives réalisées au Consortium régional de recherche en éducation entre 1998 et 2016
Bibliographic record
Abstract
Chaque année, le Consortium régional de recherche en éducation lance un appel de projets invitant les professeurs-chercheurs de l’Université du Québec à Chicoutimi et les acteurs des milieux scolaires du Saguenay–Lac-Saint-Jean, de la Côte-Nord ou de Charlevoix à s’unir afin d’étudier une problématique rencontrée dans un milieu de pratique, dans une perspective de réponse aux besoins des milieux scolaires. Notre article présente les résultats de l’analyse chronologique de 127 projets de recherches participatives soutenues financièrement par le Consortium au cours des 18 dernières années. Nous identifions les problématiques récurrentes, les principales visées des projets, les secteurs de formation les plus impliqués, etc. Cette analyse permet d’une part, de poser un regard éclairé sur l’évolution des pratiques éducatives de collaboration sur le territoire et d’autre part, de fournir des pistes de structuration et de développement pour le Consortium.
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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 | 0.044 | 0.067 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.014 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".