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Record W2135734307 · doi:10.7202/1014862ar

Moving From the Margins: Culturally safe teacher education in remote northwestern British Columbia

2013· article· en· W2135734307 on OpenAlexaffvenueabout
Edward B. Harrison, Alexander Lautensach, Verna L. McDonald

Bibliographic record

VenueMcGill Journal of Education / Revue des sciences de l éducation de McGill · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsIndigenousCultural safetyEconomic JusticeCultural diversityCulturally sensitivePedagogyMedical educationSociologyPolitical sciencePublic relationsMedicinePsychologySocial psychology

Abstract

fetched live from OpenAlex

In 2007 the University of Northern British Columbia initiated a two-year elementary teacher education program at the Northwest Campus in Terrace, British Columbia. The program was designed to meet specific community needs in the North that arise from inequities in the cultural safety of Indigenous teachers and students. The authors share three collegial inquiries into the program’s contribution toward improving cultural safety in K-12 schools and meeting social justice challenges in the region’s communities. Culturally safe allocation of space became better understood, affective learning outcomes were recognized as important determinants of cultural safety, and teacher action in classrooms towards cultural safety was scaffolded for various settings.

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)0.001
metaresearch head score (Gemma)0.001
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.167

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0190.003
Scholarly communication0.0030.001
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.163
GPT teacher head0.378
Teacher spread0.215 · 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

Citations5
Published2013
Admission routes3
Has abstractyes

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