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Record W4410524574 · doi:10.1353/cch.2025.a960513

Inuit and Empire: The Hudson’s Bay Company, “Native Welfare” in Arctic Canada and Labrador, and The Eskimo Book of Knowledge (1925–1931)

2025· article· en· W4410524574 on OpenAlexaboutno aff
George Colpitts

Bibliographic record

VenueJournal of Colonialism and Colonial History · 2025
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
FundersDartmouth College
KeywordsBayArcticEmpireThe arcticHistoryWelfareArchaeologyEthnologyGeographyOceanographyPolitical scienceGeologyLaw

Abstract

fetched live from OpenAlex

Abstract: Historians have not examined the Hudson’s Bay Company’s (HBC) “Native Welfare” program undertaken by its Development Department from 1926 to 1931, and the work of George Binney, who consolidated the company’s humanitarian and health initiatives in these years into a London-directed social engineering program. His book, The Eskimo Book of Knowledge , published by the HBC in 1931 in both English and Inuktitut, and Native Welfare itself, was largely developed to address problems perceived in the company’s newly acquired Moravian mission trade, but discursively, the health, welfare and social programming it advanced targeted all Inuit in Canada’s north. Similar to other corporate welfare programs developed by firms in North America and Europe, Native Welfare attempted to raise the health, morale and productivity of Inuit. But Binney’s book encouraged Inuit to self-identify as citizens of the British Empire. The HBC’s Native Welfare likely supported if not provided the ideological foundations of the Canadian state’s interventionist development programs in the Arctic after World War II.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.977
Threshold uncertainty score0.592

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0230.015
Scholarly communication0.0070.003
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.012
GPT teacher head0.291
Teacher spread0.280 · 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.

Study designQualitative
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
Published2025
Admission routes1
Has abstractyes

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