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Record W3095700257 · doi:10.3138/ecf.33.1.1

Truth and Reconciliation in Eighteenth-Century Literature: The Case of the “Monster Brandt”

2020· article· en· W3095700257 on OpenAlexaffvenueabout
Nikki Hessell

Bibliographic record

VenueEighteenth-Century Fiction · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsGrand River Hospital
Fundersnot available
KeywordsDepictionDiplomacyIndigenousMohawkContext (archaeology)MonsterBattlePoetryHistoryScholarshipTributeSovereigntyLawLiteratureArt historyArchaeologyArtPolitical sciencePhilosophyPolitics

Abstract

fetched live from OpenAlex

Thomas Campbell’s “Gertrude of Wyoming” (1809) plays an important and overlooked role in diplomacy between Indigenous peoples and Britain. The poem fictionalizes the Battle of Wyoming, a historical event in the American War of Independence, but includes a depiction of Joseph Brant, a real Mohawk leader. This depiction was contested by Brant’s son John when he travelled to England in 1821–22, but scholarship on this event has not located John Brant’s engagement with Campbell’s poem within the wider diplomatic mission he was undertaking. This article argues that the poem should be read within the context of Campbell’s understanding of Indigenous diplomacy, John Brant’s role as a diplomat for Six Nations of the Grand River, and modern processes of Truth and Reconciliation in Canada. It concludes that Campbell’s response to John Brant, which included a public letter of apology, connects with contemporary settler evasiveness about Indigenous sovereignty.

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)0.007
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.228
Threshold uncertainty score0.735

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0610.127
Scholarly communication0.0150.007
Open science0.0020.005
Research integrity0.0060.008
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 head0.011
GPT teacher head0.214
Teacher spread0.203 · 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 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
Published2020
Admission routes3
Has abstractyes

Explore more

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