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Record W2149513838 · doi:10.26522/brocked.v21i1.233

Keeping First Nations in Their Place–The Myth of “First Nations Control of First Nations Education”: A Commentary

2011· article· en· W2149513838 on OpenAlexafffundvenueabout
Ron Phillips

Bibliographic record

VenueBrock Education Journal · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsNipissing University
FundersAboriginal Affairs and Northern Development CanadaIndigenous and Northern Affairs Canada
KeywordsGovernment (linguistics)Economic growthPublic administrationMythologyPolitical scienceControl (management)Developing countrySociologyEconomicsManagement

Abstract

fetched live from OpenAlex

The federal government of Canada has constitutional responsibility for First Nations education. There is no evidence that the federal government has attempted to develop a comprehensive First Nations education system. Most studies have found serious flaws in the current realities faced by First Nations children attending First Nations-controlled schools throughout Canada (e.g., low levels of academic achievement, lack of second-level specialist support, inadequate school facilities, and low teacher pay). These difficulties are not found in provincial schools in which the federal government supports First Nations students. Despite its poor track record in First Nations education, the federal government remains convinced that it knows what is best for First Nations children attending First Nations schools across Canada. First Nations educational involvement, knowledge and expertise are not really considered. The idea of "First Nations control of First Nations education" is really meaningless. This paper critiques the current education system and makes recommendations.

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)0.015
metaresearch head score (Gemma)0.034
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.957
Threshold uncertainty score0.918

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.034
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0200.043
Scholarly communication0.0110.013
Open science0.0090.005
Research integrity0.0520.075
Insufficient payload (model declined to judge)0.0040.001

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 head0.019
GPT teacher head0.289
Teacher spread0.270 · 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
GenreCommentary

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

Citations1
Published2011
Admission routes4
Has abstractyes

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