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Record W7140152277

Denesułıne Oral Histories of Wood Buffalo National Park

2023· book· en· W7140152277 on OpenAlexaboutno aff
Athabasca Chipewyan First Nation, Sabina Trimble, Peter Fortna

Bibliographic record

VenueOpen MIND · 2023
Typebook
Languageen
FieldArts and Humanities
TopicOral History, Memory, Narrative Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsNational parkContext (archaeology)TreatyColonialismOral historyGovernment (linguistics)Economic Justice
DOInot available

Abstract

fetched live from OpenAlex

Wood Buffalo National Park is located in the heart of Dënesųłıné homelands, where Dene people have lived from time immemorial. Central to the creation, expansion, and management of this park, Canada’s largest at nearly 45, 000 square kilometers, was the eviction of Dënesųłıné people from their home, the forced separation of Dene families, and restriction of their Treaty rights. Remembering Our Relations tells the history of Wood Buffalo National Park from a Dene perspective and within the context of Treaty 8. Oral history and testimony from Dene Elders, knowledge-holders, leaders, and community members place Dënesųłıné voices first. With supporting archival research, this book demonstrates how the founding, expansion, and management of Wood Buffalo National Park fits into a wider pattern of promises broken by settler colonial governments managing land use throughout the twentieth and twenty-first centuries. By prioritizing Dënesųłıné histories Remembering Our Relations deliberately challenges how Dene experiences have been erased, and how this erasure has been used to justify violence against Dënesųłıné homelands and people. Amplifying the voices and lives of the past, present, and future, Remembering Our Relations is a crucial step in the journey for healing and justice Dënesųłıné peoples have been pursuing for over a century.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.050
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0480.002

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 head0.123
GPT teacher head0.303
Teacher spread0.180 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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