Arts-based health research and academic legitimacy: transcending hegemonic conventions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Using the Canadian context as a case study, the research reported here focuses on in-depth qualitative interviews with 36 researchers, artists and trainees engaged in ‘doing’ arts-based health research (ABHR). We begin to address the gap in ABHR knowledge by engaging in a critical inquiry regarding the issues, challenges and benefits of ABHR methodologies. Specifically, this paper focuses on the tensions experienced regarding academic legitimacy and the use of the arts in producing and disseminating research. Four central areas of tension associated with academic legitimacy are described: balancing structure versus openness and flexibility; academic obligations of truth and accuracy; resisting typical notions of what counts in academia; and expectations vis-à-vis measuring the impact of ABHR. We argue for the need to reconsider what counts as knowledge and to reconceptualize notions of evaluation and rigor in order to effectively support the effective production and dissemination of ABHR.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.023 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it