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Record W6886056961 · doi:10.14288/cjne.v38i1.196575

Editorial: Indigenous Teacher Education and Teacher Education for Indigenous Education

2021· article· en· W6886056961 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Collections · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousIndigenous educationTeacher educationCommissionTraditional knowledgeEducation policy

Abstract

fetched live from OpenAlex

National studies and policy statements continue to recommend an increase to the numbers of Indigenous teachers, establishment of Indigenous teacher education programs, and preparation of non-Indigenous teachers to address Indigenous education in more effective ways, through instruc­tion and parental/community engagement, according to the 1972 IndianControl of Indian Education: Policy Paper (National Indian Brotherhood), the 1996 Royal Commission on Aboriginal Peoples (Minister of Supply and Serv­ices); and the 2010 Accord on Indigenous Education (Association of Canadian Deans of Education).Over the past 40 years and more, Indigenous teacher education pro­grams have been established in universities across Canada but very little exists in the literature about these important programs and their innovations, challenges, and impact. Teacher education programs have begun to include required Indigenous education courses for all teacher candidates and new courses or approaches about Indigenous education based on Indigenous knowledge systems. We need to know more about how these courses are being received and what impact they have on teacher candidates.

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)0.006
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.994
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.029
Meta-epidemiology (narrow)0.0040.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0040.002
Science and technology studies0.0060.005
Scholarly communication0.0090.006
Open science0.0050.002
Research integrity0.0230.024
Insufficient payload (model declined to judge)0.0230.015

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 head0.015
GPT teacher head0.339
Teacher spread0.324 · 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 designNot applicable
Domainnot available
GenreEditorial

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
Published2021
Admission routes1
Has abstractyes

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