Post-<i>Kiobel v. Royal Dutch Petroleum Co.</i>: Is Canada Poised to Become an Alternative Jurisdiction for Extraterritorial Human Rights Litigation?
Bibliographic record
Abstract
The globalization of business affects the lives of citizens around the globe, both positively and negatively. With multinational corporations transcending national boundaries with their business operations comes the risk of adverse human rights impacts, particularly in regions of the world with high conflict, instability, and low governmental capacity. The risk of human rights violations has led to an increased emphasis on corporate social responsibility measures at industry, national, and international levels. One such protective measure includes statutory grants of jurisdiction to courts to adjudicate claims brought by foreign nationals alleging wrongdoings abroad in the defendant’s home jurisdiction. This measure allows foreign plaintiffs who have suffered abuse at the hands of a multinational corporation in their home jurisdiction to seek justice and compensation from that corporate defendant in the jurisdiction where the corporation’s assets are located and where the system of law is well-equipped to redress the violations. This article first explores the United States’ Alien Tort Statute and the seminal case of Kiobel v. Royal Dutch Petroleum Co. to illustrate the potential scope of extraterritorial human rights litigation in America. Then the article canvasses recent human rights litigation brought by foreign nationals in Canada and concludes with the future of Canadian law in this area.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 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".