Réflexivité et éthique du chercheur dans la conduite d’une recherche-intervention
Bibliographic record
Abstract
Ce travail s’intéresse à la phase de conduite de la recherche-intervention et s’appuie sur des retours d’expériences variés pour discuter les principes et les difficultés soulevés par cette méthodologie. La co-construction suppose un consensus entre acteurs et chercheurs, consensus difficile à atteindre et à conserver dans le temps. La pertinence de la recherche-intervention est remise en question par des soupçons de manque de rigueur et de capacités de généralisation. Sur le plan éthique, les règles d’information et de consentement informé sont impossibles à respecter alors que la confidentialité souffre de révélations déductives. Les relations entre acteurs et chercheurs dans le processus oscillent entre individus et dans le temps entre confiance, défiance et manipulations. Les apports de cet article sont notamment d’illustrer avec des pratiques et expériences concrètes le potentiel mais aussi les limites de la recherche-intervention.
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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 | 0.208 | 0.174 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.008 | 0.058 |
| Scholarly communication | 0.015 | 0.015 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.009 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".