Bioethical Policymaking for Advanced Medical Technologies: Institutional Characteristics and Citizen Participation in Eight OECD Countries<sup>1</sup>
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
Abstract Organizational characteristics of public institutions, councils, committees, and panels for bioethical deliberations were examined in eight OECD countries, that is, the United Kingdom, Germany, France, the Netherlands, Denmark, the United States, Canada, and Japan. Their jurisdiction, membership composition, modes of agenda setting, and appraisal systems were examined, as was their utilization of public involvement measures. Questionnaire surveys and structured interviews were conducted with representatives of parliamentary offices, ministries, and other institutions for ethical deliberations, both public and private, in the eight countries. Confirmation of survey results was made by close follow‐up communications. Since the early 1980s, all the countries studied have established public institutions for policy deliberation on bioethical issues. While legislatures, for example, Parliament, sometimes convene special commissions or expert panels on an ad hoc basis, most of the permanent institutions are affiliated with ministries of health, science, or technology. The composition of core panel members was quite similar across institutions as well as among countries, generally composed of 10 to 15 experts. Many institutions have experimented with some forms of public involvement measures, although public involvement is not routinely incorporated in the policy process, except in Denmark, the Netherlands, and Canada. The study describes the current public institutions and their practices for bioethical policy deliberations. Exchange of experience and knowledge among the institutions is advisable to improve their performance.
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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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