The Missed and Missing Benefits to Africa in the Absence of Harmonized International Regulation of Traditional Medicinal Knowledge
Bibliographic record
Abstract
Abstract The WHO estimates that traditional medicine(s) (TM) are used in every country around the world in some capacity and that in much of the developing world 70–95% of the population relies on these TM for primary care. It is estimated that at least 25% of all modern medicines are derived, either directly or indirectly, from medicinal plants and that in the case of certain classes of pharmaceuticals, this percentage may be as high as 60%. Some sources claim that that nearly a quarter of all pharmaceutical products worldwide are derived from plant sources. There is a global increase in interest in the use of TM and with it the global expenditure on TM. In 2005, for instance, the global market for traditional medicines was estimated at US$ 60 billion, reached US$ 83 billion in 2008 and is expected to reach US$ 114 billion by 2015. Africa prides itself as one of the most important pools for this globally important resource. Experience has, however, shown that both at national and at international levels, the continent has not yet been able to benefit from the international trade of TM. The regulation of TM is yet to become comprehensive at international and national levels. Yet, traditional medicinal knowledge has hitherto attracted only a fragmented regulatory attention by international organizations such as the WTO which focus on the various interests that TM represents. Although the harmonized regulation of the environmental, health, intellectual property, trade, cultural heritage, human rights, development and other interests on TM can be a complicated assignment, this article will attempt to show how the rules of international economic law, in tandem with other relevant international instruments, can bring benefit to the African continent by setting rules for sustainable exploitation of TM.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".