�IN CIPRO WE TRUST�: BUT HOW DO WE FEEL ABOUT OUR DRUG PATENT LAWS?
Bibliographic record
Abstract
In many ways, the terrorist attacks of September 11, 2001, crystallized national debate over drug patentsi?½both in Canada and the United States. This became clear when, at the height of the anthrax attacks in October, NBCi?½s Tom Brokaw paid the following homage to the top anti-anthrax drug: i?½In Cipro we trust.i?½ On the one hand, the public was eternally grateful for the research and development that led to the patented, life-saving CIPRO. On the other, the Canadian and United States governments insisted on obtaining national stockpiles of the drug at much-reduced prices. In fact, these conflicting attitudes toward CIPRO revealed a greater reality. Competing policy objectivesi?½providing incentives for pharmaceutical innovation while ensuring timely access to affordable medicinesi?½are the raison di?½i?½tre of many drug patent regimes, including those in Canada and the United States. Legislators and regulators alike keep searching for the best balance between these conflicting goals. This paper explores these issues through a comparative study of Canadian and United States drug patent regimes. Part II is an overview of the legislative and regulatory framework currently in place in both jurisdictions. In at least one significant respect, the regimes in Canada and the United States are unique, vis-i?½-vis the rest of the world. Pursuant to complex procedures, a drug patentee is entitled to an automatic injunction against a proposed generic competitor. Parts III and IV consider how these drug patent rules have played out in the case of CIPROi?½both before and after September 11, again in Canada and the United States. The purpose of the CIPRO case study is twofold: (1) to show how legal incentives provided to drug manufacturers can be misused, leading to possible anticompetitive outcomes; and (2) to demonstrate how current laws may not adequately address the new, suddenly pressing objective of bioterrorism defense. Finally, Part V looks at pending legislation directed at readjusting the balance between pharmaceutical innovation and generic competition.
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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 | 0.009 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.021 | 0.039 |
| Scholarly communication | 0.029 | 0.015 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".