À la recherche d’un équilibre écosystémique dans les dispositifs de recherches participatives
Bibliographic record
Abstract
Cet article a pour objectif d’apporter un éclairage aux dimensions qui unissent des chercheur·e·s et des praticien·ne·s dans les dispositifs de recherches participatives (RP), ainsi qu’aux défis méthodologiques qu’ils peuvent présenter. Une recherche participative ayant réuni enseignant·e·s et chercheur·e·s sur le thème des pratiques d’enseignement en sciences sert de point d’appui pour dégager de telles clarifications. Les résultats révèlent que l’engagement des enseignant·e·s dans la RP contribue à leur développement professionnel et améliore leurs pratiques pédagogiques. Ils révèlent également des tensions méthodologiques nécessitant des ajustements dans la conduite et le design des RP.
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 | 0.083 | 0.102 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.008 | 0.026 |
| Scholarly communication | 0.024 | 0.022 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.014 | 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".