Litigating Canada-U.S. Transboundary Harm: International Environmental Lawmaking and the Threat of Extraterritorial Reciprocity
Bibliographic record
Abstract
This Article joins a spirited debate ongoing among international law scholars. Numerous articles have debated the changing nature of international law and relations: the impact of globalization, the decline of territorial-sovereignty, the ever important role that non-state actors play, and the growing use of domestic laws to solve transboundary problems. That scholarship, however, often speaks only in general theoretical terms, and has largely ignored how these changes are playing out in countries outside the United States in ways that impact American interests.\nThis Article picks up where that scholarship leaves off. It examines one of the perennial challenges for international environmental law - how to address transboundary pollution. It does this in the context of an unlikely flashpoint, the Canada-U.S. relationship. The Article explores the possibility that Canadians will use their own domestic environmental laws in Canadian courts to remedy transboundary harm. The Article argues that in light of the recent chill in Canada-U.S. relations, the growing extraterritorial reach of U.S. environmental laws, and the recent changes in law and science that Canadians (and, in particular, those living in the province of Ontario) are likely to turn to extraterritorial environmental statutes, and then file suit under those statutes, as a means of addressing U.S. pollution that causes cross-border harm.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.029 | 0.024 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 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".