Bibliographic record
Abstract
The evidence-based movement has influenced medical research to the point that the agendas and methods of qualitative inquiry are often excluded from resources of medical granting agencies. Yet, its narrow definition of what constitutes evidence and its myopic vision about health must be challenged. In this article, the author argues that qualitative research does contribute to a reduction in morbidity and mortality without the cost in dollars and lives that are necessarily incurred in evidence-based inquiry. She asserts that we must reframe our definition of evidence to meet this new ethic of inquiry--which she calls the ultimate ethic--as a way of conducting research.
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 | 0.424 | 0.506 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.002 |
| Bibliometrics | 0.011 | 0.007 |
| Science and technology studies | 0.014 | 0.145 |
| Scholarly communication | 0.041 | 0.055 |
| Open science | 0.009 | 0.024 |
| Research integrity | 0.040 | 0.069 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".