Du « modèle du déficit » au tournant participatif en communication des risques : les luttes d’expertise au cœur de l’acceptabilité sociale des projets d’exploitation des ressources naturelles
Bibliographic record
Abstract
Contexte : Les promoteurs ont tendance à avoir recours à un « modèle du déficit » qui mise sur l’expertise pour informer et convaincre les populations du bien-fondé d’un projet. Analyse : Au moyen de deux cas discutés dans le contexte québécois puis rejetés par manque d’acceptabilité sociale, nous montrons que le modèle du déficit a à chaque fois contribué à envenimer les conflits, les populations ayant réagi à cette approche en opposant une contre-expertise crédible aux discours des promoteurs. Conclusions et implications : Notre analyse nous permet de tirer des leçons qui s’appliquent à d’autres projets. La reconnaissance d’une science plurielle, pas encore consensuelle, autour des projets discutés ainsi qu’une gestion participative du risque aurait pu mener à une discussion plus féconde sur les conditions d’acceptabilité de tels projets.
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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 | 0.016 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 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".