La co-construction d’un suivi participatif des rivières
Bibliographic record
Abstract
Notre étude explore la co-construction d’un suivi participatif des rivières au Québec impliquant un ensemble d’acteurs, dont des volontaires. Notre analyse montre une hétérogénéité d’attentes et d’enjeux par rapport au projet de suivi participatif, même si sa finalité générale, à savoir une meilleure prévisibilité des aléas de crues, n’est pas remise en cause. Nous mettons aussi en évidence certaines tensions apparues au cours du processus, notamment autour des types de mesure et de leur mise en œuvre. Les discussions et négociations entre les acteurs autour de ces questions renvoient à des points de vue situés, propres à leur positionnement qu’elles ont participé à réaffirmer ou à transformer. Étant nous-mêmes actrices dans ce processus de co-construction, cette étude est l’occasion de mener une approche réflexive sur notre posture de chercheuses impliquées.
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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.017 | 0.015 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".