Bibliographic record
Abstract
2019 marks the silver anniversary of the WTO TRIPS Agreement. Policymakers and commentators remain deeply divided about the strengths and limitations of this agreement. On the one hand, they marvel at its success in establishing international minimum standards for the protection and enforcement of intellectual property rights. On the other hand, they widely criticize the agreement for imposing high "one size fits all" standards upon developing countries.Regardless of one's perspective, the harmonization project advanced by the TRIPS Agreement, and continued through TRIPS-plus bilateral, regional and plurilateral agreements, has been at the forefront of the international intellectual property debate. While this article is interested in exploring this continuously controversial project, the discussion will focus on a topic that international intellectual property scholars have underexplored: the limits to TRIPS harmonization.To help examine these limits, this article focuses on the protection of undisclosed test or other data for pharmaceutical and agrochemical products. It begins by discussing issues on which the TRIPS negotiating parties had achieved consensus or had failed to do so. The article then examines the negotiation of new international minimum standards under the TPP Agreement, the proposed RCEP Agreement and the recently completed United States–Mexico–Canada Agreement (USMCA).The article continues to identify three sets of additional complications that have affected the efforts to develop international minimum standards at both the multilateral and nonmultilateral levels. Specifically, the article examines the arrival of new technologies, new politics and new regimes. It concludes by drawing six distinct lessons regarding the TRIPS harmonization project.
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 | 0.080 | 0.165 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.008 | 0.040 |
| Scholarly communication | 0.030 | 0.035 |
| Open science | 0.007 | 0.019 |
| Research integrity | 0.016 | 0.029 |
| Insufficient payload (model declined to judge) | 0.010 | 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".