Bibliographic record
Abstract
In Nevsun Resources Ltd. v. Araya, the Supreme Court of Canada declined to dismiss a series of customary international law claims brought by Eritrean refugees against a Canadian mining corporation for grave human rights abuses committed in Eritrea. In doing so, the Supreme Court opened the possibility of a novel front for transnational human rights litigation: common law tort claims based on customary international law. Under the doctrine of adoption, customary international law is directly incorporated into the Canadian common law. However, Canadian courts have not yet upheld a private right of action for violations of customary international law. Writing for a divided court (5–4), Justice Abella allowed the plaintiffs’ claims to proceed, finding that it is not “plain and obvious” that the plaintiffs’ customary international law claims are bound to fail under either Canada's burgeoning “transnational” or “foreign relations” law, or international law itself. In reaching this conclusion, she offered a unique and overdue reflection on the role of national courts in identifying, adopting, and developing custom. A larger majority of the court (7–2) also rejected outright the application of the act of state doctrine in Canada, tracking several common law systems in limiting the doctrine in favor of human rights litigants.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".