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Record W4385523831 · doi:10.59962/9780774831857

The Iconic North

2016· book· en· W4385523831 on OpenAlexaboutno aff
Joan Sangster

Bibliographic record

VenueUniversity of British Columbia Press eBooks · 2016
Typebook
Languageen
FieldSocial Sciences
TopicHistorical Influence and Diplomacy
Canadian institutionsnot available
Fundersnot available
KeywordsGeography

Abstract

fetched live from OpenAlex

Recent archaeological discoveries in the polar region have reanimated stock images of the intrepid explorer who braves the elements to bring modernity to a frigid northern wasteland. The Iconic North reveals that ideological assumptions, economic priorities, and a shift in government strategy in the postwar era all influenced how northern culture was represented in popular Canadian imagery. Whether it was film, television, or women’s autobiographies, the “primitive” North was often portrayed as the mirror opposite to the “modern” South. In crisp and elegant prose, Joan Sangster redirects current debates about the geopolitical prospects of the North by addressing how women and gender relations have played a key role in the history of northern development.Drawing on archival and cultural sources, Sangster shows how gender, race, and colonialism shape our understanding of northern peoples, economies, and government policy. This work reveals how assumptions about both Indigenous and non-Indigenous women shaped gender, class, and political relationships in the circumpolar north – a region now commanding more of the world’s attention.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.832
Threshold uncertainty score0.335

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.007
Scholarly communication0.0070.003
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0330.005

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 head0.218
Teacher spread0.200 · 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 designTheoretical or conceptual
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
Published2016
Admission routes1
Has abstractyes

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