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Record W3195473320

SECOND PRIZE A Force in Adazi: Strategic Deterrence by Denial

2021· article· en· W3195473320 on OpenAlexaffvenueabout
Major Andrew McGregor

Bibliographic record

VenueJournal of military and strategic studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean and Russian Geopolitical Military Strategies
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsDenialDeterrence theoryAlliancePolitical scienceTreatyDeterrence (psychology)North Atlantic TreatyMandateUnderpinningExtant taxonPolitical economyLaw and economicsLawInternational tradeSociologyBusinessEngineering
DOInot available

Abstract

fetched live from OpenAlex

As a founding North Atlantic Treaty Organization (NATO) member, Canada sustained combat forces in Europe throughout the Cold War. Since 2017, Canada has once again deployed combat forces along the Alliance’s eastern flank and opposite a revanchist Russia. Canada leads the enhanced Forward Presence (eFP) Battlegroup based in Adazi, Latvia, with the mandate to deter and/or defeat adversarial incursions. This paper argues that Canada’s eFP mission is a prudent contribution to NATO’s strategic deterrence of the Russian threat. Introducing a novel strategic deterrence framework, this paper covers the extant Russian threat, the theory underpinning NATO’s deterrence, and the implications of deterring the Russian threat. This analysis reveals that: the Russians are still the most significant threat to NATO, and by extension Canada; the eFP mission is an effective deterrence by denial mechanism; and Canada’s eFP leadership is a prudent contribution to collective security.

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)0.005
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: Empirical
Teacher disagreement score0.194
Threshold uncertainty score0.386

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0050.004
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.055
GPT teacher head0.316
Teacher spread0.262 · 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
Published2021
Admission routes3
Has abstractyes

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