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Record W2235857247 · doi:10.55016/ojs/sppp.v8i1.42537

Canada, The Law of the Sea Treaty and International Payments: Where Will The Money Come From?

2015· article· en· W2235857247 on OpenAlexaboutno aff
Wylie Spicer

Bibliographic record

VenueThe School of Public Policy Publications · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicInternational Maritime Law Issues
Canadian institutionsnot available
Fundersnot available
KeywordsTreatyPaymentLawPolitical scienceEconomicsLaw and economicsBusinessFinance

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.822
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.023
GPT teacher head0.267
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2015
Admission routes1
Has abstractyes

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