MétaCan
Menu
Back to cohort
Record W7123661485 · doi:10.25071/28169344.156

In Defence of Critical Literacy Pedagogy

2025· article· W7123661485 on OpenAlexaffabout
Wendy Moffatt

Bibliographic record

VenueYU-WRITE Journal of Graduate Student Research in Education · 2025
Typearticle
Language
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsYork University
Fundersnot available
KeywordsTransformative learningCritical literacyLiteracyImmigrationRelevance (law)Critical theoryCultural diversity

Abstract

fetched live from OpenAlex

This paper critically examines four major traditions of literacy pedagogy: didactic, authentic, functional, and critical, to evaluate their effectiveness in supporting the academic needs of immigrant students in Canadian schools. While didactic approaches emphasize the transmission of standardized knowledge, and authentic and functional models promote real-world relevance and skill application, these traditions do not sufficiently confront the systemic inequities that shape immigrant learners’ experiences. In contrast, a critical literacy framework, informed by the works of Freire, Giroux, and other scholars, offers a more transformative orientation because it foregrounds power, identity, and social justice. Integrating perspectives from multiliteracies theory, the paper also argues that immigrant students’ diverse linguistic and cultural repertoires expand what counts as literacy, challenging monolingual and deficit-based assumptions that often govern classroom practice. Drawing on culturally responsive pedagogy, the paper demonstrates how instructional approaches that value students’ lived experiences and community knowledge foster agency, engagement, and academic success. Supported by existing research and reflective classroom insights, the analysis also acknowledges limitations inherent in reflective methodology. The paper concludes by outlining implications for classroom practice, policy development, and future research in increasingly diverse Canadian educational contexts.

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)0.013
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.357
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.005
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
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 head0.347
GPT teacher head0.706
Teacher spread0.359 · 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 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 routes2
Has abstractyes

Explore more

Same venueYU-WRITE Journal of Graduate Student Research in EducationSame topicMultilingual Education and PolicyFrench-language works237,207