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Record W2906358389 · doi:10.18733/cpi29448

Cedar, Tea and Stories: Two Indigenous Women Scholars Talk About Indigenizing the Academy

2018· article· en· W2906358389 on OpenAlex
Elizabeth Brulé, Ruth Koleszar-Green

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCultural and Pedagogical Inquiry · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsYork UniversityQueen's University
Fundersnot available
KeywordsIndigenousStorytellingRedressIndigenous educationCollective actionSociologyCollective memoryCurriculumTraditional knowledgePedagogyGender studiesPolitical scienceMedia studiesNarrativeLawArtLiterature

Abstract

fetched live from OpenAlex

In an effort to redress the educational needs of Indigenous peoples as part of the Truth and Reconciliation Commission of Canada’s call to action (2015), two Indigenous colleagues, Elizabeth Brulé and Ruth Koleszar-Green, came together to engage in a collective reflection on what Indigenizing the curriculum has meant to each of them. Through a collective dialogue that affirms that knowledge is created through our individual and collective storytelling, they discussed the challenges and successes that Indigenous women have encountered in their attempts to indigenize the curriculum over the past decade in the province of Ontario, Canada. Collaborative work such as this has not only provided them with an enriching intellectual and collective experience but has also given them cause for hope in their pursuit for truth and reconciliation. Through this collective dialogue, issues of Indigeneity, pedagogy, reconciliation and sisterhood are discussed.

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.

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)0.001
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.784
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0150.002
Scholarly communication0.0000.001
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 head0.352
GPT teacher head0.477
Teacher spread0.125 · 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