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Walking the Tightrope: Exploring ‘Risky’ Issues and Discomfort in the Higher Education Classroom

2025· book-chapter· en· W4416201834 on OpenAlexaff
Fin Cullen, Michael Whelan, Mike Seal

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicEducational Theory and Curriculum Studies
Canadian institutionsSt. Mary's University
Fundersnot available
KeywordsNexus (standard)Higher educationWork (physics)DutyFace (sociological concept)Politics

Abstract

fetched live from OpenAlex

Abstract Recently, there has been much public, political and scholarly concern over the tensions between academic freedoms and effective pedagogies, student requirements and responsibilities for learning and their rights as ‘consumers’. Working with uncomfortable issues or ‘risky’ issues is at the nexus of these possibly competing narratives. Drawing on theoretical work on pedagogies of discomfort and critical dialogue with higher education (HE) youth work lecturers, the authors consider what counts as pedagogically discomforting in and beyond the classroom and slippages between issues deemed ‘emotional’, ‘sensitive’ and ‘controversial’. A specific tension in preparing students for professional practice is that HE pedagogues face a challenging dual duty of care to students and practice settings and the concurrent need to assess and prepare students to engage in sensitive arenas of practice. The authors ask how discomfort could be ethically handled within professional training contexts and what are the key institutional implications for enabling meaningful pedagogies of discomfort and challenge?

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)0.006
metaresearch head score (Gemma)0.007
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 score0.017
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0130.036
Scholarly communication0.0170.011
Open science0.0020.013
Research integrity0.0050.010
Insufficient payload (model declined to judge)0.0050.001

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 head0.068
GPT teacher head0.349
Teacher spread0.280 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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