Maximizing the differentiation principle in regional IP treaties to advance food security: Limitations in West Africa's regional IP and trade regime
Bibliographic record
Abstract
Abstract In this article, I examine whether the contemporary regional intellectual property (IP) agreements negotiated by West African countries are more suitable than multilateral agreements to advance food security in the region, based on the provisions they make for applying the differentiation principle. In this paper, the term “West Africa” is used to designate the 15 countries that are members of the Economic Community of West African States (ECOWAS), the major regional organization in the area (The founding members of ECOWAS were: Benin, Côte d'Ivoire, Gambia, Ghana, Guinea, Guinea‐Bissau, Liberia, Mali, Mauritania [left 2002], Niger, Nigeria, Senegal, Sierra Leone, Togo, and Burkina Faso [which joined as Upper Volta]. Cape Verde joined in 1977). By reviewing relevant literature and theories, I propose that the human right to development as a differentiating paradigm may be applied in IP regulation, without compromising the requirement of nondiscrimination in IP regimes. I argue that human rights linked to the food security should be differentiated from the proprietary rights granted in IP. After critical doctrinal analysis of West Africa's regional agreements related to IP rights and food security, I conclude that rather than maximising the adoption of the differentiation principle to advance the regions food security, these treaties are surprisingly less flexible than multilateral agreements, creating further challenges for food security in the region. Consequently, I propose an alternative regional framework for differentiation, that allows for differentiation between IP and human rights norms based on the instrumentalist approach to law, as being more suitable for advancing development and food security in West Africa.
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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 | 0.016 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.015 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".