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Record W2756194237

“There are no shortcuts”: The Long Road to Treaty 7 Education

2017· dissertation· en· W2756194237 on OpenAlexfundaboutno aff
Tarisa Dawn Little

Bibliographic record

VenueUniversity Library - University of Saskatchewan (University of Saskatchewan) · 2017
Typedissertation
Languageen
FieldSocial Sciences
TopicInternational Law and Aviation
Canadian institutionsnot available
FundersGovernment of CanadaLakehead UniversityAustralian GovernmentUniversity of Regina
KeywordsTreatyPolitical scienceTransport engineeringEngineeringLaw
DOInot available

Abstract

fetched live from OpenAlex

Treaty 7 was signed at Blackfoot Crossing in 1877. According to one Indigenous signatory, Chief Crowfoot of the Niisitapi, treaty commissioners in attendance stated the treaty stood in perpetuity: “As the long as the sun is shining, the rivers flow, and the mountains are seen,” the Tsuut’ina, Stoney Nakoda, and Blackfoot Confederacy: Kainai, Piikani, and Siksika agreed to share the landscape of what is now southern Alberta. This agreement is one of many treaties negotiated between First Nations and the British Crown. Many scholars have looked at Canadian treaties and education history as an overt attempt to erase Indigenous culture, but few have delved deeper into the systematic policies of epistemicide that took place within these negotiations and afterward. This thesis situates this historical process within the communities of Treaty 7 territory and argues that the schooling provided by the Canadian government after 1877 represents a consistent attempt to subvert Indigenous knowledge and pedagogies.

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)0.004
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.101
Threshold uncertainty score0.736

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0260.037
Scholarly communication0.0140.006
Open science0.0010.004
Research integrity0.0030.009
Insufficient payload (model declined to judge)0.0120.001

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 head0.008
GPT teacher head0.215
Teacher spread0.206 · 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
Published2017
Admission routes2
Has abstractyes

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