Questioning the Potential of the Forthcoming WIPO’s Diplomatic Conference on Intellectual Property and Genetic Resources: Endless Negotiations Coming to a Successful End?
Bibliographic record
Abstract
In July 2022, Member States of the World Intellectual Property Organization agreed to hold a Diplomatic Conference no later than 2024, for an international instrument on genetic resources and associated traditional knowledge to be concluded. This recent development could bring to an end more than 20 years of negotiations on the matter by the WIPO Intergovernmental Committee on Intellectual Property and Genetic Resources, Traditional Knowledge and Folklore. Indeed, genetic resources and associated traditional knowledge are left unregulated within the IP system and open for misappropriation through western IP concepts like the public domain. As a result, indigenous and local communities have faced biopiracy and began to demand protection for their traditional knowledge. The draft instrument to be negotiated puts forward a new mandatory international standard of disclosure of origin in relation to genetic resources and associated traditional knowledge. Through an analysis of this proposal, this essay questions its potential to become a successful tool to protect traditional knowledge related to genetic resources, reduce its misappropriation and achieve transparency within the patent system. It will be argued that the proposed instrument may well represent a prudent compromise, but the protection it offers is neither effective nor inclusive and lacks ambition.
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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 | 0.039 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.029 |
| Scholarly communication | 0.030 | 0.027 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.037 | 0.036 |
| Insufficient payload (model declined to judge) | 0.005 | 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".