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Record W2017037703 · doi:10.1017/s0032247413000466

Sector claims and counter-claims: Joseph Elzéar Bernier, the Canadian government, and Arctic sovereignty, 1898–1934

2013· article· en· W2017037703 on OpenAlexaffabout
Janice Cavell

Bibliographic record

VenuePolar Record · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsGlobal Affairs Canada
Fundersnot available
KeywordsSovereigntyGovernment (linguistics)ArchipelagoRhetoricHEROPolitical scienceHistoryLawSociologyLiteraturePoliticsPhilosophyArchaeology

Abstract

fetched live from OpenAlex

ABSTRACT Many writers have presented Joseph Elzéar Bernier (1852–1934) as a hero whose key role in establishing Canada's sovereignty over the Arctic islands was unjustly downplayed by the government he served. According to this view, the sector claim that Bernier made on 1 July 1909 is the true foundation of Canada's title to the archipelago. This article draws on government files to assess civil servants’ attitude to his sovereignty-related activities. It also describes the role played by James White, whose more sophisticated and effective sector concept predated Bernier's and served as the basis for the official sector claim made in June 1925. The evidence indicates that government officials in the 1920s were well justified in their doubts about Bernier's pretensions. However, even though they rejected his version of the sector theory and resented the campaign of self-glorification on which he embarked after his retirement, their personal relations with him were good, and they took considerable trouble to ensure what they considered to be an appropriate degree of recognition for him. The article therefore clarifies the differences between Bernier's rhetoric and reality, particularly with regard to the sector principle.

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)0.006
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 score0.083
Threshold uncertainty score0.604

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0220.018
Scholarly communication0.0060.002
Open science0.0010.002
Research integrity0.0030.004
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 head0.018
GPT teacher head0.253
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 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
Published2013
Admission routes2
Has abstractyes

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