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Record W7127096144 · doi:10.18357/wg24202223

“Discovering” Inuit Women

2023· article· W7127096144 on OpenAlexafffundabout
Maura Hanrahan

Bibliographic record

VenueWestern Geography · 2023
Typearticle
Language
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of Lethbridge
FundersUniversity of Lethbridge
KeywordsColonialismPossession (linguistics)ArcticWifeWhite (mutation)Jurisdiction

Abstract

fetched live from OpenAlex

Geraldine Moodie arrived in the Arctic in 1904 as part of a Canadian expedition charged with extending Canadian sovereignty. As the wife of the expedition’s leader, Moodie normalized colonial men who usually appeared without their families, shaping the Arctic as asite of heroic masculine performance. As a professional photographer and as a western woman, Moodie established relationships with Inuit women. Her studio work created images of Inuit women that would become popularized and associated with the Arctic and Canada’s possession of the north. Rooted in Fanon’s, Said’s, and Smith’s understandings of the processes of colonialization, including European concepts of “discovery,” Geraldine Moodie can be said to have “discovered” Inuit women, presenting them to her western audience as different, exotic, decontextualized and othered. This archives-based study explores the gendered role of Moodie, a colonial woman, in the absorption of Inuit and their land into Canadian jurisdiction and the “discovery” and “creation” of Inuit women in the colonial imagination.

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: Empirical
Teacher disagreement score0.611
Threshold uncertainty score0.773

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0320.012
Scholarly communication0.0060.004
Open science0.0020.007
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.032
GPT teacher head0.333
Teacher spread0.301 · 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

Citations0
Published2023
Admission routes3
Has abstractyes

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