Emerging Scholars Series: A Sui Generis Regime for Traditional Knowledge: The Cultural Divide in Intellectual Property Law
Bibliographic record
Abstract
Traditional knowledge can be protected, to some extent, under various intellectual property laws. However, for the most part, there is no effective international legal protection for this subject matter. This has led to proposals for a sui generis regime to protect traditional knowledge. The precise contours of the right are yet to be determined, but a sui generis right could include perpetual protection. It could also result in protection for historical communal works and for knowledge that may be useful but that is not inventive according to the standards of intellectual property law. Developing countries have been more supportive of an international traditional knowledge right than developed countries. At the same time, developing countries have been critical of the impact of intellectual property rights on social issues such as access to medicines and access to educational materials. In light of developing country concerns about the negative effects of strong global intellectual property rights, this paper uses a development-focused, instrumentalist approach to assess the implications of a sui generis traditional knowledge right. It concludes that some of the measures sought may not achieve the desired outcome. Although intellectual property can play a role in protecting traditional knowledge, a sui generis intellectual property style right may hinder the equity-oriented goals of some traditional knowledge communities.
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 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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".