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Record W4414071315 · doi:10.1177/17461979251356891

Journalism education as a site for civic reasoning

2025· article· en· W4414071315 on OpenAlex

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEducation Citizenship and Social Justice · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsJournalismCurriculumCivicsMoral reasoningTechnical JournalismQualitative researchCitizen journalismCivic engagement

Abstract

fetched live from OpenAlex

Journalism education can prompt young people to ask critical questions about their school and civic environments. The National Academy of Education (NAEd) recently released a report called Educating for Civic Reasoning and Discourse , in which they issue a call for educators to teach civic reasoning skills. This qualitative research study investigates an original multimedia journalism curriculum in a Grade 10 New Media course in British Columbia, Canada and explores students’ participation in civic reasoning practices. This curriculum was implemented three times between 2021 and 2022. Thirty-one students between 15 and 19 years old participated in the study. Three elements of civic reasoning are analyzed within students’ journalism stories: revising assumptions, moral resistance, and identifying the collective “we.” Participants’ journalism stories illuminate opportunities and tensions for civic reasoning pedagogy, including how to entertain multiple perspectives while still enacting moral resistance to harmful narratives.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.632
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
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 head0.055
GPT teacher head0.418
Teacher spread0.363 · 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