Contraband tobacco on post-secondary campuses in Ontario, Canada: analysis of discarded cigarette butts
Bibliographic record
Abstract
BACKGROUND: No studies to date have assessed young adults' use of First Nations/Native tobacco, a common form of contraband tobacco in Canada. This study examined the proportion of First Nations/Native cigarette butts discarded on post-secondary campuses in the province of Ontario, and potential differences between colleges and universities and across geographical regions. METHODS: In 2009, discarded cigarette butts were collected from high-traffic smoking locations at 12 universities and 13 colleges purposively selected to represent a variety of institutions from all 7 health service regions across Ontario. Cigarette butts were identified as First Nations/Native tobacco if they were: known First Nations/Native brands; had names not matching domestic and international legally-manufactured cigarettes; had no visible branding or logos. RESULTS: Of 36,355 butts collected, 14% (95% CI = 9.75-19.04) were First Nations/Native. Use of this tobacco was apparent on all campuses, accounting for as little as 2% to as much as 39% of cigarette consumption at a particular school. Proportions of First Nations/Native butts were not significantly higher on colleges (M = 17%) than universities (M = 12%), but were significantly higher in the North region. CONCLUSIONS: The presence of cheap First Nations/Native (contraband) tobacco on post-secondary campuses suggests the need for regulation and public education strategies aimed to reduce its use. Strategies should account for regional variations, and convey messages that resonate with young adults. Care must be taken to present fair messages about First Nations/Native tobacco, and avoid positioning regulated tobacco as a healthier option than contraband.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".