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Record W7051880353

Overview: Will Great Power Politics Threaten Arctic Sustainability?

2020· article· en· W7051880353 on OpenAlexaboutno aff

Bibliographic record

VenueeYLS (Yale Law School) · 2020
Typearticle
Languageen
FieldEngineering
TopicPlasma Diagnostics and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsArcticThe arcticPosition (finance)SovereigntyPoliticsGreat powerFishingEconomic power
DOInot available

Abstract

fetched live from OpenAlex

The eight Arctic states (Canada, Denmark/Greenland, Finland, Iceland, Norway, Sweden, the Russian Federation, and the United States) wish to maintain a position of preeminence when it comes to dealing with matters of Arctic Ocean governance. However, major non-Arctic states, while recognizing the sovereign rights of the coastal states in their economic zones and on their continental shelves, have growing interests in the maritime Arctic relating to activities such as commercial shipping, oil and gas development, fishing and ship-based tourism. They are increasingly claiming to have a legitimate interest in being consulted when it comes to addressing matters relating to the governance of such activities. Many questions arise from these new formulations: What is the appropriate mechanism for introducing the concerns of the non-Arctic North Pacific countries in forums dealing with Arctic issues? Can they achieve a significant voice in the deliberations of the Arctic Council? Can they address these issues through other mechanisms?

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)0.002
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0030.002
Scholarly communication0.0070.006
Open science0.0010.002
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0170.005

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 head0.013
GPT teacher head0.233
Teacher spread0.220 · 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
GenreReview

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

Citations0
Published2020
Admission routes1
Has abstractyes

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