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Record W254370014

Securitization of the Northwest Passage: The Sino-Japan Relationship and the Role of Reconciliation in the Opening of the Arctic to Transshipment of Commerce and the Exploitation of Resources

2011· article· en· W254370014 on OpenAlexaboutno aff
Kevin Cooney

Bibliographic record

VenueSSRN Electronic Journal · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGeopoliticsSecuritizationTransshipment (information security)ArcticThe arcticChinaCompetition (biology)GeographyPolitical scienceEconomyInternational tradeBusinessEconomicsOceanographyLawEcologyEngineeringFinanceArchaeology
DOInot available

Abstract

fetched live from OpenAlex

Due to the ongoing retreat of the Arctic Icecap caused by global climate change, the once fabled “Northwest Passage” between Europe and Asia is now becoming a reality. Complicating matters is the fact that Russia, Norway, Denmark, Iceland, Canada, and the United States all have various competing claims to the newly opening summer sea lanes and the newly accessible carbon resources that lie under the sea. Japan and China are two of the primary economic beneficiaries of these newly opened sea lanes and resources. However the history between these two nations presents an environment of mutual mistrust and competition. The geopolitics of transarctic shipment will bring these two nations into closer contact and expose economic and military vulnerabilities to the other. This paper will examine the potential for the Sino-Japanese relationship to move past its history into a period of reconciliation based on cooperation and the mutual need to securitize the Arctic and the fabled Northwest Passage for the economic benefit of both nations.

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)0.002
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: Empirical
Teacher disagreement score0.959
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.010
Scholarly communication0.0050.004
Open science0.0000.005
Research integrity0.0010.002
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 head0.021
GPT teacher head0.256
Teacher spread0.235 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

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