Encouraging Environmentally Sustainable Growth in Canada
Bibliographic record
Abstract
This paper analyses aspects of natural resource policy and environmental policy in Canada.In the taxation of resource-based activities, the management of water supply and the Atlantic fisheries management, the paper finds that there are incentives that may lead to overexploitation, over-harvesting or over-use, with possible harmful environmental consequences.Water prices are kept low, especially for agricultural use, exacerbating water availability problems in some areas, whereas the ban on bulk water removal and exports reveals a high implicit valuation of water.The use of economic water pricing and transferable water rights in some areas would establish more consistent incentives.The evolution of the crisis in the Atlantic fisheries illustrated the problems of balancing short-term adjustment costs against long-term sustainability.A more precautionary approach in setting total allowable catches and the removal of incentives for labour to remain in the sector may be needed.Canada also faces a number of challenges for environmental policy, in particular to deal with toxic substances, air pollution and climate change mitigation.Objectives and intermediate targets may be better defined, and some institutional features may have reinforced the usual difficulty faced by environmental policy of imposing costs on particular sectors in order to provide diffuse benefits to the public.The frequent recourse to voluntary agreements has not proved effective in dealing with toxic substances or greenhouse gas emissions.A greater use of economic instruments would improve the cost-effectiveness of environmental policy.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".