SEN WANG Industry, Trade and Economics
Bibliographic record
Abstract
En Colombie-Britannique, l’analyse économique n’a pas ou peu été utilisée dans l’application des règle-ments destinés à protéger la nature. Cet article analyse les règlements faisant partie du Code de Pratiques Forestières de la Colombie-Britannique. Les estimés des coûts annuels du Code vont de 492.4 à 696.3 millions de dollars. Du côté des bénéfices, les bénéfices récréatifs vont de 3.2 à 12.6 millions de dollars par année alors que les bénéfices de conservation pourraient s’élever de 85 à 385 millions de dollars. Les béné-fices sociaux sont inférieurs aux coûts. In British Columbia, regulations to protect nature have been implemented with little or no economic analysis. This paper provides an analysis of one set of regulations, British Columbia’s Forest Practices Code. Annual costs of the Code are estimated to be $492.4 to $696.3 million. On the benefit side, recreation benefits are estimated to be $3.2 to $12.6 million per year, while annual non-use or preservation benefits could take on values from $85 to $385 million. Social benefits are less than costs.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.069 | 0.005 |
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".