Interrogating Ourselves: Reflections on Arts-Based Health Research
Bibliographic record
Abstract
This article is deliberately unconventional in style and reflects a conversation between us—Katherine, senior scientist/principal investigator and Michael, research coordinator—as we embark on an arts-based health research study to explore the theoretical, methodological and ethical challenges faced by scientists, artists and trainees who are "doing" arts-based health research (ABHR). Our narrative is based on reflexive and observational field notes that we kept during the research process. We draw on ELLIS and BOCHNER's (2000) autoethnographic practices of writing reflexively about the ways in which the self informs one's work as a researcher. As a beginning, we each reflect upon our own perspectives on the importance of the arts in our lives. We then move to a conversation between us regarding using the arts in the process of both doing research and disseminating research that illustrates some of the key issues in the field. URN: http://nbn-resolving.de/urn:nbn:de:0114-fqs1401106
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.
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 | 0.064 | 0.092 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.056 | 0.123 |
| Scholarly communication | 0.030 | 0.021 |
| Open science | 0.007 | 0.042 |
| Research integrity | 0.015 | 0.032 |
| Insufficient payload (model declined to judge) | 0.006 | 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".