Bibliographic record
Abstract
Editor—Singer and Benatar's editorial on revisions of the Declaration of Helsinki proposes “capacity development,” defined as an increased number of professionals trained in ethics.1 Although this is indeed a step that needs to be taken, I cannot agree that it alone will advance the cause of ethical research, especially with the plans that the authors propose. The assumption that having more trained people will change the system satisfies a necessary but not sufficient criterion. The fact that there are more doctors in the developing world today than there were 20 years ago does not mean either that the practice of medicine is better or that health needs are addressed. It depends on what these people trained in ethics do, where they do it, how they sustain their efforts, and how they integrate their contributions within the overall health development of nations. The numbers and budgets presented in the proposal are simply arbitrary—they are not defended and so are difficult to evaluate. If $100m is available, what are the alternative pathways for investment for the developing world? If one considers all the health and staffing needs then the need for ethics training may not be the most important: community health workers, trained birth attendants, and others may be higher on the list. Another major issue is where the money goes. Implicit in the editorial is that the money will have to go to training centres in the West. This means that 90% of the money is not going to the developing world—a feature of “aid” well known to those in the South. The editorial severely underplays the role of other stakeholders. The importance of roles for professionals from a wide variety of disciplines, of decision makers, of community leaders, and of business leaders in shaping the practice of ethics in the South needs to be recognised. A “global alliance for health ethics” and the proposed influence on the World Bank and World Trade Organisation are only distant visions. Is this the most effective or most efficient way to achieve that vision? Activists, lobbyists, and social scientists will beg to differ. As long as ethics is viewed as something that is only for ethicists, or for those who have only been trained, it will never have the profound influence we all hope that it will have in both the developing and developed world.
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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 | 0.033 | 0.147 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.008 | 0.014 |
| Insufficient payload (model declined to judge) | 0.094 | 0.058 |
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".