Ethical questioning in arts and health-based research: propositions and reflections
Bibliographic record
Abstract
Ethical questioning is a framework for considering the ethical implications and practices in research and is used as a tool for thinking about the connections between art and health. It enables researchers and practitioners to gain a deeper understanding of the emotional dimensions in the field of art and health. In this paper, we propose that ethical questioning, grounded in the principles of ethics of care, can foster a more reflexive and holistic approach to understanding the concept of well-being. We also propose that adopting ethical questioning as a methodology, which requires intentional self-reflection and recognition of positionality, can expose and challenge conventional knowledge hierarchies, resulting in more ethical research outcomes and relationships between researchers and participants. Ultimately, our hypothesis proposes that ethical questioning holds the potential to offer an actionable practice that demonstrates ethics of care.
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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 | 0.167 | 0.153 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.019 | 0.096 |
| Scholarly communication | 0.022 | 0.022 |
| Open science | 0.004 | 0.016 |
| Research integrity | 0.014 | 0.021 |
| Insufficient payload (model declined to judge) | 0.003 | 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".