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Record W2977274155 · doi:10.1163/15718085-23441076

Unlocking the Arctic’s Resources Equitably: Using a Law-and-Science Approach to Fix the Beaufort Sea Boundary

2019· article· en· W2977274155 on OpenAlexaboutno aff
Pieter H.F. Bekker, Robert van de Poll

Bibliographic record

VenueThe International Journal of Marine and Coastal Law · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsUnited Nations Convention on the Law of the SeaMaritime boundaryArcticLaw of the seaInternational lawLawBoundary (topology)Political scienceJurisprudenceBeaufort seaOceanographyGeographyGeologyPublic international law

Abstract

fetched live from OpenAlex

Abstract This article analyses the unresolved maritime boundary situated in Arctic waters in the Beaufort Sea, between Canada and the United States through an integrated law-and-science approach incorporating new imagery technology. Resolving the Canada-United States disagreement over the Beaufort Sea boundary based on modern geo-scientific technology and the three-step delimitation methodology developed in the jurisprudence of international courts and tribunals could serve as a catalyst for the peaceful and equitable resolution of all other unresolved boundaries in the Arctic Ocean. This includes the boundaries involving Russia, which can claim more than 40 per cent of the Arctic shoreline. Given that the United States is not a party to the United Nations Convention on the Law of the Sea, this article focuses on mechanisms available to Canada and the United States under general international law and by applying ‘best law’ and ‘best science’.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.292
Threshold uncertainty score0.580

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.002
Science and technology studies0.0150.041
Scholarly communication0.0170.006
Open science0.0030.009
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.025
GPT teacher head0.304
Teacher spread0.279 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations2
Published2019
Admission routes1
Has abstractyes

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