Quand les recherches en sciences sociales s’invitent dans la gestion de l’eau
Bibliographic record
Abstract
La gestion de la qualité de l’eau est soumise à deux injonctions : un impératif scientifique et un impératif participatif. Au travers de notre expérience de chercheuses en sciences sociales engagées dans quatre démarches de protection associant des projets de recherche souvent pluridisciplinaires, cet article propose un retour réflexif sur les attentes exprimées par rapport à notre participation, ainsi que sur l’évolution de notre positionnement. Il apparaît alors que la place des chercheurs en sciences sociales n’est jamais totalement acquise, parce qu’elle produit des connaissances essentiellement dialogiques, dont les objets se déplacent et se transforment au fil des enquêtes et des interactions avec les porteurs d’enjeux. C’est finalement moins par l’intervention directe que par la réorientation de nos questions de recherche vers des problématiques liées à ces enjeux que nous avons pu partiellement contribuer aux dispositifs de gestion des pollutions diffuses d’origine agricole.
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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 | 0.061 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.012 | 0.039 |
| Scholarly communication | 0.021 | 0.015 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.010 | 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".