Bibliographic record
Abstract
On November 16, 2023, the International Court of Justice voted 13 – 2 in favor of issuing a binding Order in the case of Canada and the Netherlands v. Syrian Arab Republic. The Order adopted two provisional measures, which require Syria to prevent acts of torture and other cruel punishment, ensure that its officials and organizations do not commit torture or other cruel punishments, and preserve any evidence related to the allegations of the case. A Request for the Indication of Provisional Measures seeking such an order had been entered on June 8, 2023, by Canada and the Netherlands, for which oral arguments were held on October 10, 2023. The Request came alongside Canada's and the Netherlands' Joint Application instituting proceedings against Syria for violations of the Convention against Torture and Other Cruel, Inhuman or Degrading Treatment or Punishment. The Request and Application were made pursuant to Articles 36 and 41 of the Statute of the Court, Article 30 of the Convention against Torture, and Articles 73, 74, and 75 of the Rules of the Court. Vice-President Gevorgian and Judge Xue voted against both provisional measures, with Vice-President Gevorgian appending a dissenting opinion and Judge Xue appending a declaration.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.413 | 0.262 |
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".