No government is immune from tobacco industry interference: Lessons from Canada’s COVID-19 vaccine collaboration with Philip Morris
Bibliographic record
Abstract
Introduction In October 2020, the Government of Canada announced a US$130 million collaboration with Medicago Inc. to develop a new COVID-19 vaccine. Shortly thereafter, Philip Morris International (PMI) revealed that it was a major partner in the collaboration and provided a US$40 million loan guarantee to secure its involvement. The government’s collaboration with PMI represented a blatant violation of the WHO Framework Convention for Tobacco Control which prohibits tobacco industry partnerships among participating countries. The news of the collaboration was met with opposition and resistance from the global tobacco control community. Material and Methods In response to the PMI vaccine collaboration, ASH Canada and Corporate Accountability launched a global advocacy campaign in November 2020 urging the Canadian government to comply with the WHO tobacco control treaty and remove PMI as an investor. The advocacy campaign involved over 100 members of the Framework Convention Alliance (GATC) and included several high-profile interventions including news coverage, letter-writing, presentations, and a direct appeal to the delegates of the 2022 World Health Assembly, governments around the world and governmental regulatory agencies (i.e. FDA). Results In December 2022, Medicago revealed that PMI was ejected from the vaccine collaboration and its holdings in the company were purchased by the majority owner. Conclusions Canada is viewed as a world leader in tobacco control. If Canada is vulnerable to tobacco industry interference, then so are many countries. The WHO Framework Convention for Tobacco Control can shield participating countries from tobacco industry interference through the full implementation of Article 5.3 and its guidelines. In addition, there is an important need to implement other related articles of the treaty such as Article 19 as rapidly as possible to hold the industry accountable and deter further misconduct.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".