Achieving a Dream: Meeting Policy Goals Related to Improving Drug Access
Bibliographic record
Abstract
International experts recognize that significant inequities exist in the accessibility of life-saving medicines among poor and vulnerable populations, especially in developing countries. This article highlights that drug access even for relatively cheap medicines is out of reach for the vast numbers of global poor. This badly affects people living with HIV/AIDS who face serious obstacles in accessing ARVs. The same concerns are attributed to neglected diseases. Despite international meetings, promises from the pharmaceutical industry and a lot of media attention little has changed in the past 20 years. The accessibility gap to life-saving drugs could be reduced by the UNITAID initiative to pool patents for the many different ARVs, but the reality is that UNITAID is still a promise. To surmount this global problem of inequity requires a rethinking of traditional models of drug access and health objectives that should not be compromised by commercial interests.
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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 | 0.017 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.011 | 0.023 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.017 | 0.011 |
| Insufficient payload (model declined to judge) | 0.014 | 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".