Mining for Legal Luxuries: The Pitfalls and Potential of <i>Nevsun Resources Ltd v Araya</i>
Bibliographic record
Abstract
Abstract Globalization has effectively enabled Canada’s domestically incorporated mining companies to escape the jurisdiction of the courts of the world, allowing them to carry out human rights abuses abroad with impunity. In February 2020, however, the Supreme Court of Canada issued a landmark judgment, Nevsun Resources Ltd v Araya, which attempted to address this jurisdictional gap. This decision held that Canadian corporations could potentially be liable under domestic law for breaches of customary international law perpetrated abroad. The decision has been criticized for straying too far from a classically positivist conception of international law. This article argues that such criticisms are well founded insofar as the majority’s judgment implicitly relies on progressive human-centric theories of international law without adequately addressing how these are reconcilable with international law as it is currently applied. It then explores the ideas that drive the majority’s opinion in order to propose two alternative approaches to holding corporations accountable that are more readily reconcilable with traditional state-centric conceptions of international law. Adopting these revised approaches could less contentiously lead to corporate accountability before future domestic courts. Finally, this article considers the potential international developments and repercussions to which this and other forward-looking decisions could lead.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.015 | 0.031 |
| Scholarly communication | 0.016 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.010 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 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".