Twelve years after Canada's access to medicines regime : should South Africa follow the path?
Bibliographic record
Abstract
On 30 August 2003, the World Trade Organization decided that eligible countries without manufacturing capacities would be allowed to import generic drugs once they had been issued with a compulsory licence from an exporter country. Canada was the first country to implement this decision in its patent law and subsequently to apply it. Considering the fact that improving drug accessibility is a priority in sub-Saharan Africa, it is relevant for countries with manufacturing capacities, like South Africa, to consider implementing the August 30th decision into their legislation. This mechanism represents an opportunity for South Africa to develop its pharmaceutical industry and to increase drug accessibility in Africa. In exploring this option, the Canadian drug exportation mechanism could serve as a model for legislation in South Africa. In this article we review the Canadian experience, including the weaknesses of the Canadian platform. Based on lessons from this review, we suggest that South Africa should consider implementing a new drug exportation mechanism in its national patent law in order to rebuild its pharmaceutical manufacturing capacities and to improve access to drugs in Africa. In essence, by supplying sub-Saharan African countries, and thus using the compulsory licensing mechanism created following the Pretoria lawsuits, South Africa would close the loop.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".