Canada ane the Arctic Issue at the Third United Nations Conference on the Law of the Sea
Bibliographic record
Abstract
One of Canada's main goals at the Third United Nations Conference on the Law of the Sea was to legalize its 100-mile maritime pollution prevention zone in the Arctic. At first Canada tried to achieve this goal by seeking appropriate powers for coastal states on a global scale. However due to the strong opposition of maritime powers and insufficient support from coastal states Canada changed tactics and opted for a separate pollution prevention regime for the Arctic through a separate deal with the US and the USSR. Article 234 of the United Nations Convention on the Law of the Sea legitimized Canada's right to impose additional (environmental) requirements on foreign ships in its economic zone in the Arctic and thus to control navigation in these waters.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.004 |
| Scholarly communication | 0.011 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.012 | 0.012 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
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".