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Record W3114151453 · doi:10.3138/ecf.33.2.249

Sagoyewatha and Metonymic Being

2020· article· en· W3114151453 on OpenAlexvenueno aff
Kaitlin Debicki

Bibliographic record

VenueEighteenth-Century Fiction · 2020
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsnot available
Fundersnot available
KeywordsCovenantMetonymySovereigntyCoercion (linguistics)PoeticsSolidarityLawErasmus+SociologyAutonomyTreatyPolitical scienceMetaphorHistoryPoetryPhilosophyTheologyLinguistics

Abstract

fetched live from OpenAlex

Framed by the Haudenosaunee legal traditions of the Great Law of Peace and the Two Row-Covenant Chain Wampum, this article performs a close reading of Sagoyewatha’s (Redjacket’s) early diplomatic speeches at the Council of Tioga Point (1790) to Timothy Pickering over the murder of two Seneca citizens. I argue that American misinterpretation of the Two Row-Covenant Chain and Great Law of Peace as metaphors led them to miss opportunities for condolence, conciliation, and peaceful coexistence with their Haudenosaunee brethren. Sagoyewatha’s oratory, deeply grounded in Haudenosaunee cultural empiricism and discourses of good mindedness, respect, and strength in unity, offers an example of metonymic diplomacy and being that remains pertinent to present-day conflicts over Haudenosaunee—and more broadly, Indigenous—treaty rights, land title, self-determination, and sovereignty. I query whether the development of metonymic literacy in eighteenth-century poetics might have provided—and might still provide—settlers with a deeper understanding of their Two Row-Covenant Chain responsibilities based on a relationship of separateness, autonomy, difference, and solidarity.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.033
Scholarly communication0.0040.005
Open science0.0000.003
Research integrity0.0010.002
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 head0.018
GPT teacher head0.258
Teacher spread0.240 · 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 designTheoretical or conceptual
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

Citations1
Published2020
Admission routes1
Has abstractyes

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