Bibliographic record
Abstract
Failed in and Doha agenda, U.S. do not want to deal the issues related to IPR in the multilateral forum, but moves to the FTA mechanism. They pressed the partners to accept the IPR standards which were higher than TRIPs, and the developing countries could not reject those TRIPs Plus clauses because U.S. is the biggest market for them. But the standpoint of U.S. was not coherency in FTA policy for some domestic reasons. For example, some states of the U.S. adopted parallel import and the U.S. senate has had discussions over parallel import concerning medicine import from Canada, especially after the outbreaks of anthracnose. This kind of attitude change in the U.S. is also reflected in the FTAs, for example, instead of general prohibiton on the principle of exhaustion, the FTA prescribes a contract prohibiting parallel import between patent holders and agencies with exclusive rights. So the countries which are negotiating with U.S. would not accept any kind of demands of IPR, they can choose the proper IPR policies, especially in public health area.
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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.022 | 0.011 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".