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Record W4416768357 · doi:10.26522/brocked.v34i2.1217

Investigating Public School Language Initiatives in Northern Manitoba

2025· article· en· W4416768357 on OpenAlexvenueaboutno aff
Frank Deer

Bibliographic record

VenueBrock Education Journal · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousIndigenous languageLegislatureResource (disambiguation)Language planningIndigenous educationSchool system

Abstract

fetched live from OpenAlex

An emergent imperative in public school priorities across Canada in recent years is that of Indigenous education. An important part of this imperative, as articulated by Indigenous peoples and educational authorities, is that of Indigenous language programming. In response, some public-school districts have explored and initiated Indigenous language programs. The purpose of this study was to investigate how public-school districts have navigated and managed Indigenous language programming in northern Manitoba – one of some regions in Canada for which Indigenous language use is comparatively high. Participation was solicited from public school districts in this region that have initiated Indigenous language programming. Interviews with school administrators and educators were conducted to explore how the programs were developed, implemented and the impact they have had upon students, families, and communities. This study found that public schools in northern Manitoba have experienced some success in recent years with their respective language programming in spite of difficulties such as the availability of qualified teachers, resource procurement, and legislative limitations. Participants reported successful navigation of language-related politics, linguistic nuance related to such things as dialect use, and collaboration with their respective communities.

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)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.356
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.054
GPT teacher head0.441
Teacher spread0.387 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2025
Admission routes2
Has abstractyes

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