Don’t sacrifice generic drug industry for sake of Canada-European trade deal
Bibliographic record
Abstract
As Canada and the European Union (EU) appeared close to finalizing a Comprehensive Economic and Trade Agreement (CETA) in December 2012, Canada’s generic drug industry remained concerned about possible Canadian concessions on patent protection for brand-name pharmaceuticals. The European Commission had proposed that Canada extend intellectual property (IP) protection for brand-name drugs, which would mean a longer wait for generic versions to enter the market. “The Canadian government has said it doesn’t support these measures per se because they would drive up drug costs in our health care system,” says Jim Keon, president of the Canadian Generic Pharmaceutical Association (CGPA). “But our concern is that these proposals are still on the table; the government hasn’t ruled out accepting them as a trade-off for some other benefit — expanded access for Canadian beef exports, for example.” Mr. Keon cites a study by health economists Paul Grootendorst and Aidan Hollis, which estimated the EU proposals would delay introduction of generic pharmaceuticals by an additional 3.5 years in Canada, increasing drug expenditures by $2.8 billion a year. It has been reported that federal studies have estimated the extra drug costs would be up to $900 million each year. The Europeans are pushing patent protection that goes beyond not only current World Trade Organization (WTO) requirements, but also beyond Europe’s own IP standards, says the CGPA president. “Many brand-name drug companies are headquartered in Europe, so what they are doing is advocating on behalf of those companies and trying to get maximum profits and business for them in Canada,” he says. “Not only would these measures increase drug costs, but they would harm the generic industry in Canada — generic manufacturers would move their development and manufacturing to other jurisdictions, where they could begin exporting their products earlier.”
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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 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.014 | 0.010 |
| Scholarly communication | 0.022 | 0.011 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.017 | 0.013 |
| Insufficient payload (model declined to judge) | 0.045 | 0.018 |
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".