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Record W4401382337 · doi:10.3138/ijcs-2024-00xx-ml

“Especially in This Free Country”: Webs of Empire, Slavery, and the Fur Trade

2024· article· en· W4401382337 on OpenAlexaffvenueabout
Margaret Anne Lindsay

Bibliographic record

VenueInternational Journal of Canadian Studies · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicColonialism, slavery, and trade
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsFur tradeEmpireInternational tradeEconomicsHistoryAncient history

Abstract

fetched live from OpenAlex

Spanning the years from late 1600s and into the early 1800s “‘Especially in This Free Country:’ Webs of Empire, Slavery and the Fur Trade” challenges a historiography that positions what has come to be known as the Canadian fur trade as exceptional in its relationships between colonizers and Indigenous peoples, where interactions between Indigenous producers and non-Indigenous traders are presented as largely cooperative and peaceful and as rooted in relationships that operated in the absence of coerced or unfree labour. In fact, the fur trade, connected as it was through webs of family/business relationships to the rest of the colonial world was not exceptional. Across northern North America the fur trade world experienced the same sorts of violence, including chattel slavery, as the rest of the empires with which these webs connected. Far from absent, colonial violence was a part of the Canadian fur trade just as it was a part of empire. Located in the pre-history of Canada, this thesis responds to Harvey Amani Whitfield’s observation that, although there have been some excellent studies of slavery in Canada recently, “slavery has not become part of the Canadian national narrative” 1 by arguing that chattel slavery in the fur trade in what would become Canada was linked to the empires it was a part of, pervasive, integrated into all aspects of the fur trade, and occurred across the northern North American continent.

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 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 score0.817
Threshold uncertainty score0.901

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.031
GPT teacher head0.337
Teacher spread0.306 · 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.

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
Published2024
Admission routes3
Has abstractyes

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