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Record W4409880415 · doi:10.3138/jcs-2024-0017

“An Indian of Considerable Consequence”: British Travellers, “Big Chiefs,” and Settler Colonialism in 1790s’ Upper Canada

2025· article· en· W4409880415 on OpenAlexaffvenueabout

Bibliographic record

VenueJournal of Canadian Studies · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicTravel Writing and Literature
Canadian institutionsQueen's University
Fundersnot available
KeywordsColonialismHistoryEthnologyPolitical scienceAncient historyEconomic historyArchaeology

Abstract

fetched live from OpenAlex

This article examines the travelogues of two late eighteenth-century British travellers: Patrick Campbell and Isaac Weld. Travel writing was a pursuit intimately tied to promoting empire, and by endorsing Upper Canada as an attractive destination for British settlers, both travellers encouraged the dispossession of Anishinaabe and Haudenosaunee peoples. As tourists, Campbell and Weld were also fascinated by the idea of “Indian” chiefs. Realizing that Upper Canada was as much an Indigenous world as a British one, and recognizing the role played by the Haudenosaunee in imperial defence, they turned their fascination with chiefs to rhetorical advantage. Ignorant of actual Haudenosaunee governance, Campbell and Weld instead invested sovereignty in select Kanyen’kehaka men who conformed to their pre-conceived notions of what chiefs ought to be like. Friendship between these men and the British proved useful in travel writing, justifying British acts of settler colonialism on the basis that, unlike the Americans who waged wars to dispossess the Northwest Confederacy, the British were welcome and the moral power on the continent. The importance given to chiefs to secure this friendship reminds scholars that what Susan Hill called the “Big Chief” school of analysis has a long literary past that has historically justified empire.

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)0.000
metaresearch head score (Gemma)0.000
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.246
Threshold uncertainty score0.441

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.019
GPT teacher head0.232
Teacher spread0.212 · 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
Published2025
Admission routes3
Has abstractyes

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