Bibliographic record
Abstract
In 1987, the Commission on Health Research for Development noted that new knowledge (research) was needed to create effective action to improve the health of poor people and that it (this type of research) had been enormously neglected.1 They went on to indicate that all public health services need to embed in their plans the resources needed to carry it out. This needed to be applied across the board, and not only in low-income countries. Little has changed since 1987. In this issue of the Journal, we report a point of view that builds on this need, indicating that it is not sufficient just to carry out the research but that it needs to lead to action for change and this change must be documented.2 Moreover, the authors indicate that the process requires a formal mechanism in order for it to be monitored. Only in this way can we confirm that it leads to the desperately needed action for health. They propose a radical approach to this problem, namely that scientific journals (starting with Public Health Action [PHA]) undertake responsibility for monitoring. We fully concur with the authors that a mechanism is essential to ensure that what we say we do, we actually do. Moreover, such a mechanism would provide ‘value added’ to the research we carry out. In public health, it is important not only to identify the ‘what’ but also the ‘who’, ‘when’ and ‘where’. The real question is, how should this be done? If this were a task that the Journal were to carry out, it would need to be supported with the resources to do so. This implies several things. First, those who would carry out the task must be qualified for it if it is to have any credibility. This would imply that the Journal would need to engage (a) specialist(s) to undertake the task. Would this be ad hoc or full-time? What would the qualifications need to be? Second, as PHA operates on the revenues obtained from the authors who publish in the Journal, would we then add a surcharge to cover the costs? Obviously this would normally be a charge passed on to those who originally funded the research in most instances, but it would further distance the Journal from being able to publish original research that does not have a sponsor. We fully endorse the need for a mechanism for monitoring the actions emanating from the results of research in order to validate the benefit of this research. However, it is not clear who should do this. This is not a question that should be left dangling; it needs urgently to be addressed by an expert forum to find a way forward.
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 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 | 0.010 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".