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Record W4399284472 · doi:10.3390/rel15060677

Preservice Teacher Views on Critical Religious Literacy to Counteract Epistemic Injustice in Teacher Education Programs

2024· article· en· W4399284472 on OpenAlexafffundabout
Erin Reid

Bibliographic record

VenueReligions · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicReligious Education and Schools
Canadian institutionsSt. Mary's University
FundersUniversity of LethbridgeMcGill University
KeywordsInjusticeTeacher educationPedagogyLiteracySociologyPsychologyMathematics educationSocial psychology

Abstract

fetched live from OpenAlex

While there has been growing scholarly interest in the role of religious literacy in K-12 teacher education, scholarship on how preservice teachers understand religious literacy as an aim of social justice-oriented education remains limited. This empirical case study of one teacher education program in a Canadian university examines the perspectives of preservice teachers and how they view critical religious literacy (CRL) as a means of addressing the potential harms of religious illiteracy. Using empirical data collected in personal interviews and focus groups, this qualitative case study employed philosophical analysis centered on a theoretical framework that includes the concept of epistemic injustice. The data show that preservice educators feel unprepared to engage with religiously diverse students, to navigate issues related to religious diversity, or to respond to the potential epistemic harms of religious illiteracy, such as exclusion, discrimination, or polarization. As such, this paper contends that to reduce the potential epistemic injustices related to religious illiteracy in their programs and in K-12 classrooms, teacher educators ought to include CRL as an educational aim in preservice teacher education.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.537
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.003

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 head0.035
GPT teacher head0.430
Teacher spread0.396 · 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 designNot applicable
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

Citations3
Published2024
Admission routes3
Has abstractyes

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