Sensory Arts-Based Storytelling as Critical Reflection: Tales From an Online Graduate Social Work Classroom
Bibliographic record
Abstract
Drawing upon Heron and Reason’s (1997) participatory inquiry paradigm and extended epistemology, this article explores how six Master of Social Work (MSW) students engaged in sensory arts-based critical reflection concerning their social location, identities, social justice, and social policy. We share our process for creating sensory arts-based stories, the stories themselves, and pedagogical reflections. We elucidate how sensory arts-based storytelling allows learners to draw upon their strengths, unique perspectives, and experiences in the world, generating transformative understandings of social justice. Sensory arts-based storytelling holds potential as an interdisciplinary mode of critical reflection, generating inclusive learning environments oriented towards social change.
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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 | 0.012 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.018 | 0.032 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.004 | 0.020 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".