Bibliographic record
Abstract
Tobacco-related illnesses kill 45,000 Canadians annually – more than were killed during the six years of World War II (1). For the tobacco industry to maintain its profits, each dying smoker must be replaced by another victim. Sadly, the new conscript is usually younger than 20 years of age. Data from the 1994 Survey on Smoking in Canada (2) indicated that 84% of Canadian adults who had ever smoked began smoking before they reached age 20 years. Our society is engaged in a war against the single largest preventable cause of premature death in Canada; although death occurs after many decades, the new recruits are mostly child soldiers. Although few interventions have had a significant effect on reducing either enivronmental tobacco smoke exposure or smoking initiation in children, it appears that organized, comprehensive smoking cessation campaigns have been successful. California, Oregon and Massachusetts have seen dramatic reductions in tobacco use following coordinated and well-funded interventions (in excess of $5 per capita) (3). A Canadian consensus document that outlined the goals and strategic directions for a comprehensive tobacco control strategy was published in 1999 (4). Unfortunately, current funding levels of less than $1 per capita mean that Canadian anti-smoking initiatives remain underfunded, especially compared with the magnitude of the problem, the profits of the tobacco industry, and the revenues of federal and provincial governments. With a levy on every cigarette pack sold in Canada, the proposed Tobacco Youth Protection Act would provide realistic funding for a comprehensive approach to tobacco reduction. So how can paediatricians and other health care providers help protect children and youth from the dangers of tobacco? We have a key role to play – we have the public's trust in our offices or in the offices of legislators. We can talk with children and their parents about the proven risks of tobacco, using our personal credibility to change their lives. In our communities, we provide scientific validity to the cause against tobacco. The Canadian media have been very supportive of the message that youth are victims of a multinational industry that sees children as fair game; we should make allies of these well-meaning journalists. Whether we speak to the media or to politicians, we address the concerns of children, and not the concerns of voters or industry. It was this type of lobbying by physicians and nongovernmental organizations in Newfoundland and Labrador that resulted in the forthcoming ban on smoking in all public places that are frequented by children. Imagine the impact of such a ban nationwide. Ultimately, we must take sides in the war against tobacco. Inaction gives the tobacco industry unopposed access to child recruits, condemning hundreds of thousands of Canadian children to a premature death as adults. Implementing a comprehensive tobacco reduction strategy across Canada will, undoubtedly, save lives. What are we waiting for?
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 | 0.007 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.010 | 0.018 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.018 | 0.025 |
| Insufficient payload (model declined to judge) | 0.023 | 0.008 |
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".