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Record W2800564620 · doi:10.1111/hic3.12445

Indigenous intellectual traditions and biography in the northeast: A historiographical reflection

2018· article· en· W2800564620 on OpenAlexfundno aff
Thomas Peace

Bibliographic record

VenueHistory Compass · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsHistoriographyIndigenousBiographyColonialismHistorySovereigntyPower (physics)TRACE (psycholinguistics)Intellectual historySociologyAnthropologyGender studiesArt historyPolitical scienceLawPoliticsPhilosophyArchaeology

Abstract

fetched live from OpenAlex

Abstract Over the past two decades, a substantial literature has developed probing Robert Warrior's idea that we can trace a written Indigenous intellectual tradition back to the mid‐eighteenth century. Focused on Indigenous peoples who wrote fairly extensively, much of this literature has tended to treat the same individuals: Samson Occom, Joseph Brant, Peter Jones, William Apess, and George Copway (among others). Over the past 5 years, a series of biographies have been published on other individuals who fit within this community of intellectuals. Drawing together these two streams within the historiography, this essay probes the concept of Indigenous intellectual traditions, suggesting that scholars need to look beyond print culture. Doing so will better account for Indigenous concepts of sovereignty and territory, the involvement of women, the role of class, as well as the relationship between these traditions, historiographical practices, and settler colonial systems of power.

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)0.005
metaresearch head score (Gemma)0.005
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: Empirical
Teacher disagreement score0.172
Threshold uncertainty score0.392

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0220.023
Scholarly communication0.0070.004
Open science0.0010.005
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 head0.036
GPT teacher head0.250
Teacher spread0.215 · 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

Citations2
Published2018
Admission routes1
Has abstractyes

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