Pedagogies of discomfort and disruption: A meta‐narrative review of emotions and equity‐related pedagogy
Bibliographic record
Abstract
INTRODUCTION: Discussions about equity in professional education can evoke a range of complex emotions. Approaches to emotionally challenging pedagogies may vary across professions. Comparative explorations of these approaches may yield fresh insights that could enhance our teaching and learning strategies within health professions education. Therefore, the authors sought to explore how the professional contexts of medicine, nursing and teacher education approach the role of emotions in equity-related pedagogy. METHODS: A meta-narrative approach was utilised to synthesise existing research on the relationship between emotions and equity-related pedagogy in three different professions. Six databases were searched using key terms yielding 3102 titles. After screening, 58 articles were selected for extraction. Through coding and analysis, the authors sought to gain a deeper understanding of why emotions are relevant to equity-related pedagogy in each profession, and how each profession grapples with emotional dissonance. RESULTS: There were both contrasting and complimentary meta-narratives about emotions and equity-related learning in medicine, nursing and teacher education. All three professions viewed emotions as relevant and essential for equity-related learning. Medicine and nursing sought to make emotions accessible and explicit, while foregrounding the need for learners to build skills to understand and address emotions such as critical reflection and dialogue. Meta-narratives in teacher education were similar to medicine and nursing; however, teacher education further emphasised the role of emotions in fostering community, trust and empathy. DISCUSSION: Existing meta-narratives regarding emotions and equity-related pedagogy in health professions suggest that medicine and nursing have acknowledged the intrinsic role that emotions play in equity-related learning yet lag behind teacher education in considering the role of emotions as a socio-cultural connector and mediator.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.012 | 0.008 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".