The future of medicines use and access research: using the Journal of Pharmaceutical Policy and Practice as a platform for change
Bibliographic record
Abstract
Scientific journals are most often used to disseminate the end products of research, but also have an important role as instruments of change. One year after the launch of the Journal of Pharmaceutical Policy and Practice, the focus of articles published has been on pharmaceutical health systems research, including contemporary issues related to medicines management, socio-behavioral aspects of pharmacy and macro pharmaceutical issues. Our most cited articles ranged from those on generic medicines in Jordan [1], antibiotics sensitivity, usage and access in India and Namibia [2,3], to a review of national medicines policies around the globe [4]. At this point the Journal has successfully provided a forum to publish within its specified themes. However, given the technological and social changes in health, medicines and public policy, we are keen to promote the Journal of Pharmaceutical Policy and Practice as a platform for change, in order to advance specific agendas. We would argue that this change agenda is underpinned by the following issues:
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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 | 0.112 | 0.159 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.009 | 0.045 |
| Scholarly communication | 0.064 | 0.064 |
| Open science | 0.004 | 0.015 |
| Research integrity | 0.036 | 0.018 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".