La valeur économique pour l’amélioration de la qualité de l’eau: le cas de la rivière Magog et du lac Magog (Québec, Canada)
Bibliographic record
Abstract
L’objectif de cet article est de déterminer la volonté à payer (VAP) de la population sherbrookoise et magogoise pour l’amélioration de la qualité des eaux du lac et de la rivière Magog; ainsi que leur volonté à accepter (VAA) pour une compensation monétaire dans un scénario d’interruption du système d’épuration des eaux usées. Pour cela, nous utilisons une enquête d’évaluation contingente qui emploie le format de questionnaire VAP-VAA de type MBDC (Multiple Bounded Discrets Choices ou questionnaires à choix discrets et multi-bornes). Pour approfondir l’analyse, nous suivons la logique du modèle de Welsh et Poe (1998) pour déterminer les VAP et VAA moyennes des individus résidant autour du lac et de la rivière Magog. À cet effet, nous trouvons une VAP moyenne par habitant de 98$CA/mois, et une VAA moyenne par habitant de 758$CA/mois.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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".