Tough medicine: Ensuring access to affordable drugs requires fixing trade agreements starting with NAFTA
Bibliographic record
Abstract
The negotiation of trade agreements, which is conducted in secret, poses serious risks for the generic/biosimilar industry as the originator industry uses them as a tool to ratchet up the protection of intellectual property rights to broaden and extend their monopolies, and forcing changes in the laws and regulations of the countries as international law supersede national law. The Trans Pacific Partnership (TPP) demonstrated that the constructive engagement of the generic/biosimilar industry can make a difference in these negotiations to strike a balance that both fosters innovation while ensuring patients’ expedited access to more affordable drugs. The industry needs to be vigilant in the ongoing negotiations for the modernisation of the North American Free Trade Agreement (NAFTA) between Canada, Mexico and the United States, which will not only affect those three pharmaceutical markets, but also set a precedent for future trade negotiations.
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 | 0.023 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.013 | 0.017 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.016 | 0.013 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".