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Record W2519253613 · doi:10.7202/1037202ar

Unlocking the ‘Eskimo Secret’: Defence Science in the Cold War Canadian Arctic, 1947–1954

2016· article· en· W2519253613 on OpenAlexafffundvenueabout
Matthew S. Wiseman

Bibliographic record

VenueJournal of the Canadian Historical Association · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsSocial Sciences and Humanities Research Council
FundersWilfrid Laurier University
KeywordsCold warAppropriationArcticIndigenousWhite (mutation)Political scienceColonialismEnvironmental ethicsHistoryEthnologyLawEcologyPoliticsBiology

Abstract

fetched live from OpenAlex

Between 1947 and 1954, medical scientists in Canada received support from federal and independent agencies to conduct a series of comparative biochemical studies on Inuit and white “test subjects.” Originally conceived from a racialized intrigue in defining the vascular characteristics of cold tolerance, the Canadian defence establishment absorbed the research with the intent to apply the findings to military service work in the North. Potentially unlocking the “Eskimo” secret to cold-weather acclimatization meant scientists could devise a screening process for selecting male white bodies for Arctic service. The research took place within the edifice of colonial science, but unlike wider postwar perceptions of the Indigenous body, this article presents the concept of biological appropriation to explore the perceived value of Inuit physiology to northern defence. Interpreting experiential research on Inuit as distinct from cultural assimilation provides a broader interpretation of postwar Arctic policy, and helps discern an understudied yet important episode of the Cold War sciences in Canada.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.925
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.185
Teacher spread0.168 · 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 teacher head, not a consensus.

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

Citations11
Published2016
Admission routes4
Has abstractyes

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