Public Deliberation in Health Policy and Bioethics: Mapping an emerging, interdisciplinary field
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
For over two decades, the “deliberative turn” has rooted itself in the fields of health policy and bioethics, producing a growing body of deliberation in action and associated academic scholarship. With this growing use and study of citizen deliberation processes in the health sector, we set out to map this dynamic field to highlight its diversity, interdisciplinarity, stated and implicit goals and early contributions. More specifically, we explored how public deliberation (PD) is being experimented with in real-world health settings, with a view to assessing how well it is meeting current definitions and common features of PD. Our review provides an informative and up-to-date set of reflections on the relatively short but rich history of public deliberation in the health sector. This emerging, interdisciplinary field is characterized by an active community of scholars and practitioners working diligently to address a range of bioethics and health policy challenges, guided by a common but loosely interpreted set of core features. Current definitions and conceptualizations of public deliberation’s core features would benefit from expansion and refinement to both guide and respond to practice developments. Opportunities for more frequent cross-disciplinary and theory-practice exchange would also strengthen this field.
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 | 0.001 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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