Contraband Cigarette Purchasing from First Nation reserves in Ontario and Quebec: Findings from the 2002–2014 ITC Canada Survey
Bibliographic record
Abstract
Backround: The availability of contraband cigarettes provides incentives for price-sensitive smokers to reduce their monetary costs of smoking. The objectives of this study were to examine whether Canadian smokers' geographic proximity to First Nations reserves and attempts to quit smoking influenced the likelihood of purchasing lower-cost cigarettes from reserves. METHODS: Data were from the International Tobacco Control (ITC) Canada Survey, a prospective survey of Canadian adult smokers conducted from 2002 to 2014 using telephone and online interviewing methods. Analysis was restricted to smokers from Ontario (n=2105) and Quebec (n=1427) participating in at least one survey wave. Smokers' postal codes were used to calculate distance to the nearest reserve. Weighted logistic generalised estimating equations (GEE) regression examined the linear relationship between distance and the log odds of last purchasing cigarettes on reserve in each province. GEE models also examined the relationship between past-year quit attempts and the log odds of on-reserve purchasing. RESULTS: Controlling for other factors, from 2002-2014, smokers from Ontario who lived 10 km closer to reserves than otherwise similar smokers had significantly higher odds of last purchasing on reserve (OR ranged from 1.16 to 1.65). Distance had little effect on smokers' purchasing behaviours in Quebec. Moreover, in Ontario, for every 10 km increase in distance, smokers who did not try to quit had significantly greater odds of purchasing from a reserve than smokers who tried to quit (p=0.002). CONCLUSION: In order for tobacco taxation policies to achieve their maximal benefit, governments must limit potential sources of lower-cost cigarettes. Collaborative governance arrangements can ensure tobacco products sold on reserve to non-Indigenous people are appropriately taxed while allowing First Nations communities to keep the revenue generated by such taxes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".