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Record W2413386658

Lock, Stock, and Icebergs? Defining Canadian Sovereignty from Mackenzie King to Stephen Harper

2008· article· en· W2413386658 on OpenAlexaboutno aff
Adam Lajeunesse

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSovereigntyArcticCold warThe arcticPolitical scienceStock (firearms)LawHistoryOceanographyPoliticsArchaeology
DOInot available

Abstract

fetched live from OpenAlex

From the dawn of the Cold War, the point at which the issue of Arctic sovereignty first gained national prominence, to the present day, Canadian governments have consistently voiced their uncompromising dedication to the defence of Canada's northern heritage. However, historically, Canadian policy has never matchedits rhetoric in the Arctic. In an age where competition in the Arctic is becoming more intense, with states vying for control of vast natural resources and potential shipping lanes, the issue of Arctic sovereignty can no longer be one of secondary concern. Canada can no longer dismiss the burdens which go hand-in-hand with sovereignty. It must decide how important the Arctic tryly is to the nation and be ready to stand behind that decision.

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)0.004
metaresearch head score (Gemma)0.008
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: Other · Consensus signal: none
Teacher disagreement score0.125
Threshold uncertainty score0.905

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0390.025
Scholarly communication0.0130.006
Open science0.0020.004
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0080.000

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 head0.041
GPT teacher head0.289
Teacher spread0.248 · 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
GenreOther

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

Citations7
Published2008
Admission routes1
Has abstractyes

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Same topicArctic and Russian Policy StudiesFrench-language works237,207