Gerard V. La Forest and the Uncertain Greening of Canadian Public Law
Bibliographic record
Abstract
This tribute essay concentrates on Justice La Forest's contributions to Canadian public law in three leading environmental cases. The first was R. v. Crown Zellerbach Canada Ltd.,' where the issue was the constitutionality of federal legislation on marine pollution that applied to the dumping of material into provincial waters by a provincial undertaking. While agreeing with his colleagues that marine pollution was a matter on which the federal government could legislate, La Forest J. wrote a provocative dissent to the ruling of the court that marine pollution came within Parliament's residual authority to legislate on peace, order and good government (POGG). The second case was Friends of the Oldinan River Society v. Canada (Minister of Transport) in which La Forest J. wrote the opinion for a nearly unanimous court. It upheld the authority of the federal government to require federal departments and agencies to conduct environmental assessments before exercising regulatory powers or committing federal spending in relation to provincial projects. The third case was R. v. HydroQuebec, in which a razor-thin majority agreed with La Forest J. that the federal power over criminal law authorized the Canadian Environmental Protection Act, 19994 (CEPA), which created a broad regulatory framework for the manufacture, importation, sale, use and disposal of toxic substances.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.045 | 0.020 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.016 | 0.012 |
| Insufficient payload (model declined to judge) | 0.009 | 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".