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Record W4417333964 · doi:10.1080/00933104.2025.2587148

Between maintaining teacher impartiality and protecting student dignity: Teachers’ responses to unacceptable student speech about politically sensitive issues in France and Quebec

2025· article· en· W4417333964 on OpenAlexafffundabout
Baptiste Roucau, Bruce Maxwell

Bibliographic record

VenueTheory & Research in Social Education · 2025
Typearticle
Languageen
FieldPsychology
TopicCommunication in Education and Healthcare
Canadian institutionsUniversité de Montréal
FundersFonds de recherche du QuébecCentre National de la Recherche Scientifique
KeywordsImpartialityPower (physics)Government (linguistics)Context (archaeology)

Abstract

fetched live from OpenAlex

How should teachers respond when students make dignity-undermining comments during discussions of politically sensitive issues? This qualitative, transnational study examines how 13 secondary teachers in France and Quebec (Canada) maintain impartiality while protecting student dignity in response to unacceptable student speech. Drawing on a thematic analysis of in-depth interviews, we identify three key findings. First, teachers report using a spectrum of responses ranging from dialogical to silencing strategies, which they modulate based on the perceived extremeness of the speech. Second, teachers use impartiality deliberately as a pedagogical tool to challenge unacceptable views. Third, participants promote respect for dignity adaptively via the “political criterion,” treating it as a mandate to intervene only when dialogical strategies fail. These findings refine existing theories of teacher impartiality, disclosure, and controversial issues education, while offering transnational insights into how teachers navigate tensions between fostering open dialogue and protecting human dignity in classroom discussions.

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)0.012
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.164
Threshold uncertainty score0.970

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.114
GPT teacher head0.585
Teacher spread0.471 · 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 designObservational
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

Citations1
Published2025
Admission routes3
Has abstractyes

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