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Record W2765864208 · doi:10.21971/p7ww9r

Keeping Loyalty and Regulating Insubordination: Freemen and the Edmonton House Fur Trade, 1821-1828

2017· article· en· W2765864208 on OpenAlexaffvenueabout
Hereward Longley

Bibliographic record

VenueCrossing boundaries · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAutonomyProfitability indexDebtGeographyEconomyBusinessPolitical scienceFinanceEconomics

Abstract

fetched live from OpenAlex

This paper examines the Hudson’s Bay Company (HBC) Edmonton House Journals and district reports from 1820-1829 to assess the relationship between the HBC and Freemen over the decade immediately following the merger between the HBC and Northwest Company (NWC). I argue that although numbers of Freemen associated with Edmonton House decreased substantially as Freemen moved to the Red River and Columbia River regions after the merger, Freemen associated with Edmonton House provided an essential supply of food and fur that bolstered both the viability and profitability of the post, and served as an invaluable buffer between the HBC and Indigenous peoples. Freemen often moved fluidly between bush and post, procuring food and furs for the fort, at times engaging in contract labour around the fort, or accompanying trapping and exploration missions alongside fort employees. By the end of the decade, it appears that many Freemen were able to eliminate their debts with the HBC and establish more autonomous communities. In the fort Edmonton region, the 1820s can perhaps be viewed as a point of emergence for Freemen communities as they gained greater autonomy from fur trade companies and increased the size of their families. Growth in the independence and size of Freemen bands in the 1820s may be considered as a root of Métis ethnogenesis in the West.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.889
Threshold uncertainty score0.946

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.1130.056
Scholarly communication0.1180.001
Open science0.0000.000
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 head0.018
GPT teacher head0.273
Teacher spread0.256 · 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; both teacher heads agree on what is shown here.

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
Published2017
Admission routes3
Has abstractyes

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