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Record W2571848150 · doi:10.17103/sybil.20.11

The Arctic securitization and the crisis of multilateralism: A comparison between European countries, Canada, Russian Federation and the United States of America

2016· article· en· W2571848150 on OpenAlexaboutno aff
Diego Badell

Bibliographic record

VenueSpanish Yearbook of International Law · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMultilateralismSecuritizationPolitical scienceArcticInternational tradeEconomic historyBusinessEconomicsLawFinancial systemPolitics

Abstract

fetched live from OpenAlex

This paper provides a comprehensive review of the Securitization in the Arctic studying the impact of securitization processes into the Arctic multilateral institutions. It is expected that securitized sectors will not diminish the Arctic Countries multilateral participation meaning that States will not settle disputes outside the realm of multilateral institutions. In order to carry out this research, I am looking at the classical five securitization sectors: military, political, societal, economic, and environmental sector analysing the Arctic Countries security strategies via discourse analysis from the period 2007-2014. The analysis leads me to conclude that securitization is not diminishing multilateral participation following the premises of neoliberal theories and rejects the realist premises. Nevertheless, there is an exception; the US in the political sector is diminishing its multilateral participation.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.552
Threshold uncertainty score0.892

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.007
Science and technology studies0.0030.004
Scholarly communication0.0060.003
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.265
Teacher spread0.255 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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