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Record W4310090950 · doi:10.22584/nr53.2022.007

The Legend of Thanadelthur: Elders’ Oral History and Hudson’s Bay Company Journals

2022· article· en· W4310090950 on OpenAlexaffvenueabout
Rosalie Tsannie-Burseth

Bibliographic record

VenueThe Northern Review · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsHatch (Canada)University of Saskatchewan
Fundersnot available
KeywordsLegendIndigenousHistoryNegotiationBayOrder (exchange)Oral historyGenealogyEthnologyAnthropologySociologyPolitical scienceArt historyLawArchaeologyEcologyBusinessBiology

Abstract

fetched live from OpenAlex

This article introduces the legend of Thanadelthur, a Dene woman who had a profound impact on the Dene people in Northern Saskatchewan and Manitoba during the eighteenth century fur trade. Thanadelthur was instrumental in the negotiation of a peace treaty between the Dene and Cree, and in helping the Dene to build a trade relationship with the Hudson’s Bay Company. These actions helped to create new economic opportunities for Dene communities and a good life for Thanadelthur’s people. While Thanadelthur’s life is documented in scholarly works and Hudson’s Bay Company journals, those records do not tell the entire story. Thus, this article also recounts oral stories told by Elders and others in order to expand this legend to include the perspective of the Dene. In bringing together the reports from Dene oral historians, scholars, and other authors, this article outlines the remarkable events in Thanadelthur’s life in order to underscore her historical significance to our communities and Canada at large. This article is a chapter in the open textbook Indigenous Self-Determination through Mitho Pimachesowin (Ability to Make a Good Living), developed for the University of Saskatchewan course Indigenous Studies 410/810 and hosted by the Northern Review.Tthainaltth’er t’ą-u Cǫmpani Kǫę ha Dene chu, Ená chu ëƚëhela nį snį, t’a-u dahłëlghël nį-u; Ąƚnëdhi chu Cǫmpani Kǫę honį nįhenįla si diri bëghą honį sį. Dene ëƚëhela tl’ąghë tsádhedh k’ets’įdel nį. Tthainaltth’er Denesuline ha nįdhen-ú, la Dene ha horenįle hël, Dene doreƚti nįthen t’a Dene ts’įnį nį. Tthainaltth’ur bëghą honį ƚą, ëritƚ’is k’e tth’i hëla, ąƚnëdhi behonié tth’i ƚą sį. T’ą-u Tthainaltth’er huya, yanathë honį k’onį ha. Canada k’eyaghë náide si, Tthainaltth’er denegodhë helį kuli horįcha hołts’į nį; Dena ha.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.610
Threshold uncertainty score0.776

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0100.007
Scholarly communication0.0060.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.001

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 head0.052
GPT teacher head0.281
Teacher spread0.230 · 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
Published2022
Admission routes3
Has abstractyes

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