The International Legal Regime for Biotechnology Patenting: an Appraisal from the Standpoint of Developing Countries
Bibliographic record
Abstract
The development of biotechnology, which promises many economic opportunities, has revived the debate over the ownership of biological resources and its derivatives, as well as the sharing of the benefits which derive from its multiple applications. At the core of the debate, is the recent marriage between intellectual property rights (IPR) and international trade, within the framework of the World Trade Organization (WTO). In this context, the need of developed countries to prevent trade distortions due to the lack of adequate IPR protection in developing countries, is weighed against the need to promote local interests in these countries. However, the legal impact of recent multilateral agreements, which address biological innovations, is still subject to controversy. An assessment of these instruments reveals divergent approaches to the issues which divide the parties concerned. This results in ambiguities and conflicts with respect to relevant provisions of these agreements. From a wide range of possible solutions discussed, industrial and developing countries might consider to review the disputed provisions in a way that attempts to harmonise the agreements and render legal implications of their respective initiatives in this area more predictable.
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 | 0.018 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.015 | 0.016 |
| Science and technology studies | 0.004 | 0.013 |
| Scholarly communication | 0.017 | 0.011 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.007 | 0.007 |
| 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".