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Record W1975967143 · doi:10.1163/22116427-91000126

An International Polar Code of Navigation: Consequences and Opportunities for the Arctic

2013· article· en· W1975967143 on OpenAlexaboutno aff
Andrea Scassola

Bibliographic record

VenueThe Yearbook of Polar Law Online · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPolar codeHarmonizationArcticThe arcticPolitical scienceBusinessNegotiationInternational communityInternational tradeEnvironmental planningLawEngineeringGeographyTelecommunicationsEcology

Abstract

fetched live from OpenAlex

Abstract The Arctic regime on vessel-source pollution is currently fragmented and inadequate to tackle the emerging environmental risks. Thus, a harmonized set of norms is needed to ensure compliance with internationally recognized standards. During the IMO’s Polar Code negotiations, Canada and the Russian Federation claimed that the regulations adopted pursuant to article 234 shall not be infringed. If ratified and complied with by a large majority of the international shipping community, The Code could acquire the status of generally accepted international rules and standard (GAIRAS). It follows that a Polar Code is not likely to substitute existing national norms, nor will it impede Arctic coastal states to use article 234 in the future. The tension between harmonization and the persistence of national regulations will likely result in a partially harmonized regime. While the Code will extend environmental protection to the high seas, national regulations will be harmonized in the EEZ insofar as design, construction, equipment and manning standards are concerned. Aside from the Polar Code process, designation of Special Areas and PSSAs may integrate the future Polar Code and the national regulatory frameworks now in force. Bilateral or multilateral harmonization should not be excluded to the extent practicable.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.684
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.078
GPT teacher head0.356
Teacher spread0.277 · 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 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

Citations5
Published2013
Admission routes1
Has abstractyes

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