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Record W4386976069 · doi:10.23865/arctic.v3.30

The EU and the Arctic: European foreign policy in the making

2012· article· en· W4386976069 on OpenAlexaboutno aff
Njord Wegge

Bibliographic record

VenueArctic review on law and politics · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsArcticForeign policyPolitical scienceThe arcticMember statePoliticsState (computer science)European unionInternational tradeMember statesEconomicsLaw

Abstract

fetched live from OpenAlex

The EU is currently reviewing its interests in the High North and has recently started developing an Arctic policy. This article aims at explaining this foreign policy expansion by applying a theoretical framework consisting of three levels: (1) the internal level – viewing EU foreign policy (EFP) as the product of an “organization;” (2) the state level – in specifically accounting for the role played by external actors, primarily states; and (3) the systemic level – viewing the EU and its foreign policy as dependent on structural conditions within the global system. Through interviews, document studies, as well as existing scholarly research, the article identifies impact from all three analytical levels, including how the supranational and member-state level combined has been decisive in shaping the final policy outcome. The research identifies the crucial role played by other Arctic states, particularly Canada and Norway. Finally, on the systemic level, key conditions such as global warming and economic forces are recognized as relevant explanatory factors behind the development of the EU’s Arctic policy.

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)0.008
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0050.010
Scholarly communication0.0120.006
Open science0.0010.004
Research integrity0.0060.003
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 head0.043
GPT teacher head0.358
Teacher spread0.315 · 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 designNot applicable
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

Citations31
Published2012
Admission routes1
Has abstractyes

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