Les recherches partenariales/collaboratives : Peut-on simultanément théoriser et agir?
Bibliographic record
Abstract
Notre article interroge la montée de la recherche partenariale ou collaborative (RPC) aux côtés de la recherche universitaire « classique ». Nous nous demandons dans quelle mesure la pratique de la recherche partenariale contribue à l'émergence de processus de collaboration, de médiation, de partage de connaissances, voire de « co-construction » de connaissances. La recherche partenariale vise à favoriser une collaboration continue et engagée de membres provenant de divers milieux, de la recherche mais aussi du terrain ou de la pratique. Nous montrons que les différences de rôles, de contextes de travail, de temporalités, d’identité peuvent expliquer les difficultés de mise en place d’échanges entre les divers milieux (universitaire, communautaire, syndicaux, ou autres, selon les cas) et nous identifions aussi les avantages de la RPC et les conditions permettant de profiter de ces avantages.
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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 | 0.052 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.009 | 0.046 |
| Scholarly communication | 0.028 | 0.038 |
| Open science | 0.004 | 0.015 |
| Research integrity | 0.005 | 0.006 |
| 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".