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Record W4412929381 · doi:10.55146/ajie.v54i1.1044

Uncomfortable truths: Teaching about race and anti-Indigenous racism in the classroom

2025· article· en· W4412929381 on OpenAlexaff
Cheryl Ward, Melody E. Morton Ninomiya, Michelle Firestone

Bibliographic record

VenueThe Australian Journal of Indigenous Education · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicCritical Race Theory in Education
Canadian institutionsWilfrid Laurier UniversitySt. Michael's HospitalInstitute of Indigenous Peoples' Health
Fundersnot available
KeywordsIndigenousRacismRace (biology)SociologyProject commissioningPublishingGender studiesCritical race theoryPedagogyMedia studiesPolitical scienceLawEcology

Abstract

fetched live from OpenAlex

Anti-Indigenous racism education is often framed as a way to improve non-discriminatory care for Indigenous peoples. This study asked: What happens when anti-Indigenous racism is taken up by educators? What makes it challenging to manage in an adult classroom? What strategies are (un)successful? Ten adult educators participated—Indigenous (n = 4), White (n = 3) and non-Indigenous People of Colour (n = 3)—in either an interview or focus group. A phenomenological approach guided interpretation of participant narratives. Findings revealed persistent anti-Indigenous racist violence in adult educational settings. Successfully challenging anti-Indigenous racism required deep educator knowledge, self-awareness, cultural humility and strong facilitation skills. The traumatic toll on Indigenous educators and differing responses to resistance highlighted how racism is experienced and addressed differently by Indigenous, non-Indigenous People of Colour and White educators. This study provides empirical evidence for the need for pedagogical strategies that improve cultural safety, support educators and meaningfully confront anti-Indigenous racism in adult education classrooms.

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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
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 science0.0010.000
Research integrity0.0000.001
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 head0.016
GPT teacher head0.373
Teacher spread0.357 · 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.

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
Published2025
Admission routes1
Has abstractyes

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