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Record W4416943947 · doi:10.1177/1086296x251401121

Reading and Equity in Teacher Education: An Exploratory Study

2025· article· en· W4416943947 on OpenAlexafffund
Rachel Heydon, Lori McKee, Elizabeth Akiwenzie, Emma Cooper, Bronwyn Johns, Pamela J. McKenzie, Marianne McTavish, Sandra Poczobut, Carla Ruthes Coelho, Melody Viczko, Zheng Zhang

Bibliographic record

VenueJournal of Literacy Research · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicCritical Race Theory in Education
Canadian institutionsSt. Francis Xavier UniversityUniversity of British ColumbiaUniversity of SaskatchewanWestern University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsEquity (law)Reading (process)Exploratory researchNexus (standard)Qualitative researchEducational equityTeacher educationHigher education

Abstract

fetched live from OpenAlex

Reading is central to higher education, but requires increased pedagogical and research attention. Practice and knowledge gaps have created threats to equity, though the precise nature of the reading/equity nexus in higher education is unknown. The Reading Pedagogies of Equity Project, a professional learning program and study designed with teacher educators, sought to produce insights into equity and reading in higher education. Oriented through critical posthumanism and a speculative pedagogies of qualitative inquiry methodology, the research team generated data with nine teacher educator participants. Data sources included the program pedagogies, discussions, and artifacts, plus pre- and post-program interviews. Data were analyzed through a thinking with theory approach focused on entanglement, diffractive reading, and enacted agency. The study identified textual, contextual, pedagogical, and readerly (im)materialities in academic reading that (dis)able opportunities for equity and the processes for producing this knowledge. Findings are significant for educators wanting to promote equity in/through reading.

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)0.005
metaresearch head score (Gemma)0.013
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 score0.007
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0070.004
Scholarly communication0.0050.003
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.154
GPT teacher head0.623
Teacher spread0.469 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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