Canada, The Law of the Sea Treaty and International Payments: Where Will The Money Come From?
Bibliographic record
Abstract
Canada is a party to the United Nations Convention on the Law of the Sea, having ratified it in 2003. This Convention requires parties to it to make payments in respect of oil production on their continental shelves beyond 200 miles, to an international organization which is then tasked with distributing such payments to selected States parties to the Convention, taking into account the interests of the least-developed countries.* Canada has a number of offshore licenses in the area of the continental shelf to which these payments will apply. The amount of the payments is based on the total production at the site. After 12 years of production, the Convention stipulates that the amount of the payment is seven percent of production, and remains at that percentage for the rest of the producing life at the site. It is anticipated that Canada may be the first state to be required to make these payments. The annual cost to Canada of this obligation will be in the millions of dollars. At present Canada has no framework in place to source these funds. There is a well-developed royalty regime in the offshore, but it does not contemplate this substantial requirement. This paper discusses how this requirement developed in international law, the role of Canada in its development, and how it has come to be that there is no contemplation of this requirement in the current framework of Canadian law. The paper also discusses potential solutions.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.019 | 0.013 |
| Scholarly communication | 0.017 | 0.009 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".