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Record W4401121226 · doi:10.7202/1112549ar

Reconciling the Ledger: The Rupert’s Land Purchase, Settler Capitalism, and Indigenous Dispossession on the Prairies

2024· article· en· W4401121226 on OpenAlexvenueaboutno aff
Elizabeth McKenzie, Ian Mosby

Bibliographic record

VenueJournal of the Canadian Historical Association · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicAmerican Environmental and Regional History
Canadian institutionsnot available
Fundersnot available
KeywordsLedgerIndigenousCapitalismEconomic historyGeographySociologyPolitical scienceEconomicsEcologyLawFinanceBiology

Abstract

fetched live from OpenAlex

This article examines one of the greatest land grabs in history and what may represent one of the single greatest transfers of wealth from Indigenous peoples to a private company: the so-called Rupert’s Land Purchase of 1870. By comparing the lands and money given to the Hudson’s Bay Company following Confederation for the transfer of Rupert’s Land to Canada with the lands and money set aside for First Nations signatories of Treaties 1–7 (1871–77) and the Métis Nation under the Manitoba Act of 1870, we attempt to establish what this looked like in material terms. In addition to highlighting the scale of wealth dispossession that occurred in both quantitative and qualitative terms, this article is primarily concerned with Canada’s actual implementation of these agreements. In recognizing the treaties beyond their written documents, this article seeks to challenge some of the popular narratives surrounding the Rupert’s Land Purchase and its significance in histories of stolen Indigenous land and wealth.

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)0.003
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 score0.379
Threshold uncertainty score0.762

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0170.038
Scholarly communication0.0060.003
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.008
GPT teacher head0.182
Teacher spread0.173 · 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
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the Canadian Historical AssociationSame topicAmerican Environmental and Regional HistoryFrench-language works237,207