Bibliographic record
Abstract
It is impossible to know in advance what legal form, if any, Canada’s emissions trading regime will ultimately take. However, the current Conservative government’s explicit policy of replicating the United States’ greenhouse gas reduction goals and legislation offers some clues. Based on the government’s legislation and rulemaking thus far, the emissions trading regime that emerges in the short term may be an informal collection of emissions trading provisions contained in industry-specific regulations passed under the Canadian Environmental Protection Act. Such a regime may not be the most effective in staving off climate change, but it will impose additional costs on certain activities and, consequently, increase the possibility of a legal challenge from one of the provinces or from an economic actor sanctioned for failing to comply with the regime. Considering the likelihood of such a constitutional challenge, this paper explores the potential constitutional bases for such a regime, focusing on the three heads of federal power: criminal law, trade and commerce, and the “national concern” branch of the “peace, order, and good governance” power. It concludes that only one of these heads of power, trade and commerce, will likely support the contemplated emissions trading regime.
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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.014 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".