Canada and the Polar Code: Balancing Unilateralism and Multilateralism in the Regulation of Arctic Shipping Special Issue on Arctic and Antarctic Regions: New Challenges for Ocean Governance
Bibliographic record
Abstract
This article discusses Canada's implementation of the Polar Code recently adopted by the International Maritime Organization and how this instrument triggered an implementation strategy that produced a high degree of harmonization with the code. This discussion is undertaken against the historical backdrop of unilateral legislation and emergence of Article 234 of the United Nations Convention on the Law of the Sea, 1982. Canadian expectations in the development of the Polar Code and the extent to which these were addressed in the final product and eventually implemented are analysed. The article reflects on how the Canadian approach to the implementation of the Polar Code has produced a pragmatic balance between unilateralism and multilateralism. While Canada has increasingly engaged with regional and global fora on shipping governance issues, there will likely be continued use of Article 234.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.017 | 0.021 |
| Scholarly communication | 0.016 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.006 |
| 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".