The 2011 Canada-European Union Comprehensive Economic and Trade Agreement: an economic impact assessment of the EU’s proposed pharmaceutical intellectual property provisions
Bibliographic record
Abstract
Canada and the European Union (EU) are currently negotiating a comprehensive economic and trade agreement. This study examines how the proposed EU language in the draft negotiating text would affect the pharmaceutical market in Canada. Our key finding is that the EU proposals will considerably lengthen the period of exclusivity for innovative drugs in Canada, so that Canada would have the most extensive structural protection of innovative drugs of any country in the world. Payers – consumers, businesses, unions, and government insurers – would face substantially higher drug costs as exclusivity is extended on top-selling prescription drugs, with the annual increase in costs likely to be about $2.8 billion per year. The EU proposals would lead to an average extension of pharmaceutical exclusivity likely to be over 2 years. The purpose of exclusivity rights granted to innovators is to create an incentive for research and development investments into new drugs. However, the amount of additional investment in pharmaceutical innovation that would result from the implementation of the EU’s proposed pharmaceutical intellectual property provisions would likely be a small fraction of the additional costs to Canadians.
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 | 0.024 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.018 | 0.003 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".