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
The interpretive and subjective nature of qualitative research has led to growing utilization of arts-based strategies for data collection, analysis and dissemination. The defining characteristic of all such strategies is that they are largely subjective and intended to invoke personal responses in the ‘audience.’ Following that direction, many qualitative researchers are using metaphor to capture themes emerging from their analysis. In this article, we explore ethical aspects of using metaphor in describing results of qualitative health research and illustrate some of the complexities using a case study of research conducted by one of the authors. Our analysis is designed to sensitize researchers and ethics reviewers to some unique ethical issues inherent to this approach towards data analysis and presentation. Issues related to participant dignity, respect and vulnerability led us to suggest that researchers should take these points into consideration in designing their research and seeking informed consent. Metaphors can be linguistic devices, but also conceptual aids that help develop patterns in analysis or that facilitate re-interpretation. However, there is a thin line between artistic licence for better expression and distorting the participants’ actual experience and meanings. Researchers, and reviewers, must be aware of the danger to participant dignity and integrity when aesthetics overshadow actuality. The use of metaphor may also trigger tensions between researchers and participants, especially if member checking is used. The implications of participant withdrawal must be considered and conveyed to ethics reviewers and participants. It is important to have a plan in place for dealing with some of these issues. These should be detailed in the proposal and communicated to participants. Institutional research ethics boards should, on their part, be prepared to ask questions if such details are lacking in the proposal.
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 | 0.587 | 0.692 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.005 | 0.015 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.017 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it