L’éthique au-delà du protocole déontologique. À chaque terrain, son éthique ?
Bibliographic record
Abstract
La recherche ethnomusicologique interpelle l’éthique dans une optique à la fois vaste et ciblée à laquelle le protocole déontologique universitaire, du moins tel qu’il est conçu actuellement, ne répond que partiellement. S’il existe un consensus autour des conditions d’enquête dans la communauté scientifique, ces conditions sont-elles suffisantes pour mener une recherche qui serait éthiquement correcte ? Telle est la question centrale à laquelle l’auteure tente de répondre. Après avoir livré sa conception du terme éthique, l’auteure montre à travers une série d’exemples issus du terrain que ce qui prime en matière d’éthique est d’abord et avant tout la mise en place d’une qualité relationnelle, ce qui place forcément les acteurs de la recherche dans une démarche qui va au-delà d’un protocole. En conclusion, l’article aborde de manière critique la « déontologisation » des pratiques de recherche.
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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 | 0.536 | 0.413 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.011 | 0.063 |
| Scholarly communication | 0.018 | 0.021 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.008 | 0.019 |
| 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; 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".