Embodied Reflexivity Through the Arts: An Introduction
Bibliographic record
Abstract
Emerging from a global health crisis that shone the light on the effects of alienation, isolation, and physical and spiritual vulnerability, we wondered what we might offer to re/center humanness and remind us of individual and collective possibilities to create positive change. With this call in our hearts and bodies, our special issue began to take shape. We are three scholars at different stages of our careers and with intersecting areas of expertise, but who are all grounded in reflexive ways of being, embodied ways of knowing, and artful ways of engaging. We acknowledge the scholars(hip) in each of these distinct areas and are grateful for the foundation on which we build. Thus, with our collective yearnings to centre an integrated way of at/tending to an emergent process of re/making and re/imagining knowledge, we offer this special issue with three intentions: to advance arts-based educational research in developing critical, social, and relational consciousness; to evoke/provoke embodied pedagogical practices that transform teaching/learning; and to contribute to re/humanizing education (Lyle, 2022) and social justice reform.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.030 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.011 | 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".