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Record W4210317353 · doi:10.21810/jicw.v4i3.4154

Arctic Security and Defence in a Competitive World

2022· article· en· W4210317353 on OpenAlexaffvenueabout
Andrea Charron

Bibliographic record

VenueThe Journal of Intelligence Conflict and Warfare · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsPresentation (obstetrics)ArcticCompetition (biology)Political scienceThe arcticInternational securityOceanographyPublic administrationEcologyMedicineGeology

Abstract

fetched live from OpenAlex

On November 22, 2021, Dr. Andrea Charron, Director for the Center for Defence and Security Studies at the University of Manitoba, presented on Arctic Security and Defence in a Competitive World at the 2021 CASIS West Coast Security Conference. The primary focus of Dr. Charron’s presentation was on three key areas of questioning the competitiveness of international order within Arctic security and defence. These areas were: competition, decision makers, and fora for navigating competition. The presentation was followed by a question and answer period with questions from the audience and CASIS Vancouver executives.

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)0.006
metaresearch head score (Gemma)0.004
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 score0.064
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0190.007
Scholarly communication0.0180.005
Open science0.0010.005
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0220.004

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 head0.039
GPT teacher head0.326
Teacher spread0.287 · 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
Published2022
Admission routes3
Has abstractyes

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