Qualitative evidence, knowledge translation, and policy-making, with reference to health technology assessment
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
Although efforts to draw qualitative evidence into health-related policy-making and health technology assessment (HTA) processes have increased in recent years, the range of sources consulted are still limited and the theoretical foundations for consulting them are underdeveloped. This essay builds on such recent scholarship, first, by opening conventional models of knowledge translation up to the possibilities of qualitative evidence, and second, by demonstrating the utility of this wider range of qualitative evidence, signally that of humanities scholarship, in health-related policy-making. The second of these will consist of two themes – pain and narrativity – that will illustrate both the particular complexity of policy-making in HTA, whereby social, ethical, and moral variables are at play, and the mitigating affect humanities scholarship, at its best, might have on this fraught process.
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 | 0.016 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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