Clarifying the Liability Risk of Shipping in the Canadian Arctic
Bibliographic record
Abstract
In the coming years the Arctic Ocean will become navigable for significant periods of time. Now is the time to consider the legal regime that will govern the arctic region, and the recent Polar Code is a major international step in that direction. Among the areas that need further attention before the Arctic becomes a major commercial highway is shipping liability. In particular, Canadian law may hold cargo owners liable for ship owners’ mistakes, errors, and omissions leading to oil spills in the Canadian Arctic. This peculiar cargo owner liability may be an uninsurable risk, and is therefore potentially destabilizing to firms that may not even appreciate their risk. Rather than getting rid of this protection entirely, however, this article proposes a solution to bring this facet of Canadian law into harmony with the Polar Code, preserving the additional protection afforded by cargo owner liability, while tempering it with principles from the Polar Code itself.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.009 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".