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Record W4214920311 · doi:10.25071/2561-5467.302

Setting an Arctic Course: Task Force 80 and Canadian Control in the Arctic, 1948

2011· article· en· W4214920311 on OpenAlexafffundvenueabout
Peter Kikkert, P. Whitney Lackenbauer

Bibliographic record

VenueThe Northern Mariner / Le marin du nord · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsTransport Canada
FundersSocial Sciences and Humanities Research Council of CanadaArcticNetJohns Hopkins University
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Utilisant pour cette étude le cas de la Force opérationnelle 80 et la mission de réapprovisionnement dans le grand nord de 1948, les auteurs examinent de façon critique les relations Canadien-Américaines dans l'Arctique au début de la guerre froide.Les données archivistiques indiquent que, plutôt que de sacrifier la souveraineté dans l'intérêt de la sécurité continentale, le gouvernement canadien a scruté et a surveillé les activités de défense américaines dans l'Arctique pour s'assurer qu'il maintienne un niveau de contrôle approprié.Il y avait des inadvertances, des caprices et des malentendus de part et d'autre, mais les officiels ont compris des leçons importantes de la mission de 1948 qui ont été appliquées aux activités ultérieures de réapprovisionnement, prenant le cap vers un rapport opérationnel de plus en plus fonctionnel.On the afternoon of 30 July 1948, the icebreakers United States Ship (USS) Edisto and United States Coast Guard Ship (USCG) Eastwind left the anchorage at Thule, Greenland and set a course for the coast of Ellesmere Island.Along with a third vessel, the cargo ship USS Wyandot, which was on its way to Resolute Bay, the little group was called Task Force 80.Its mission seemed straightforward: resupply the joint Arctic weather stations set up the previous summer and establish a new one on the northern tip of Ellesmere.2 The voyage, however, proved anything but simple.By the next morning the ships were cautiously picking their way through loose and scattered floe ice.Their helicopters scouted for the best routes, but by evening the two icebreakers ran into thick pack ice as they neared central Kane Basin.Their progress 1

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)0.003
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 score0.103
Threshold uncertainty score0.744

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0220.004
Scholarly communication0.0040.001
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.018
GPT teacher head0.252
Teacher spread0.234 · 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

Citations1
Published2011
Admission routes4
Has abstractyes

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