Bibliographic record
Abstract
Although there are many important intellectual property and public health developments in the United States, the domestic debate remains surprisingly disconnected from the international debate. To help bridge this disconnect, this Article discusses the interrelationship between intellectual property and public health in the context of communicable diseases. This type of disease is intentionally picked to highlight how developments abroad could easily affect what happens at home, and vice versa.The first half of this Article recounts three distinct stories about viruses responsible for AIDS, SARS, and the avian influenza (H5N1). The first story focuses on the ongoing developments within the WTO concerning efforts to address the access-to-medicines problems in relation to HIV/AIDS and other pandemics. The second story documents the unusual race among research and health institutions in Canada, Hong Kong, and the United States to patent technologies involving the isolated gene sequences of the SARS coronavirus. This story also explores the use of patenting as a defensive measure and the development of patent pools as a solution to prevent the creation of a patent thicket. The final story examines the recent efforts by Indonesia, India, and other members of the Non-Aligned Movement to claim sovereignty over viruses found within their jurisdictions.The second half of the Article draws seven important lessons from the three earlier narratives to advance a new, integrated approach to setting international intellectual property norms. Applying the proposed approach to these lessons, this Article focuses on three sets of issues that often come up in the international norm-setting process: negotiation gains, the negotiation process, and negotiated outcomes. The Article concludes by reminding readers that the international debate could easily spill over into the domestic debate, and vice versa.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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; both teacher heads agree on what is shown here.
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".