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Record W2744397900 · doi:10.20360/g2bt17

Using a Graphic Novel Project to Engage Indigenous Youth in Critical Literacies

2017· article· en· W2744397900 on OpenAlexafffundvenue
Alexis Brown, Deborah L. Begoray

Bibliographic record

VenueLanguage and Literacy · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicLiteracy, Media, and Education
Canadian institutionsUniversity of Victoria
FundersCanadian Institutes of Health Research
KeywordsIndigenousSociologyLiteracyCritical pedagogyPedagogyCritical literacyEquity (law)Action researchMathematics educationPolitical sciencePsychology

Abstract

fetched live from OpenAlex

The purpose of this paper is to present the experiences of Indigenous youth when a critical literacies/Indigenous knowledges (IK) approach was used in a graphic novel creation project. We conducted research over a six-week period in two alternative high schools in British Columbia. In this paper, we look primarily at research findings from the Indigenous program. We analyzed classroom observations, the graphic novels, and transcripts of semi-structured interviews according to four principles of critical literacy: understanding power, control, and equity of information; collaboration using multiple perspectives; authentic and multimodal learning; and enacting social change and civic engagement.

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)0.008
metaresearch head score (Gemma)0.009
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 score0.016
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0160.021
Scholarly communication0.0080.004
Open science0.0020.012
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.001

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 head0.104
GPT teacher head0.376
Teacher spread0.272 · 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

Citations13
Published2017
Admission routes3
Has abstractyes

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