ORIGINAL PAPER Marijuana and tobacco use among young adults in Canada: are they smoking what we think they are smoking?
Bibliographic record
Abstract
Abstract The authors characterized marijuana smoking among young adult Canadians, examined the co-morbidity of tobacco and marijuana use, and iden-tified correlates associated with different marijuana use consumption patterns. Data were collected from 20,275 individuals as part of the 2004 Canadian Tobacco Use Monitoring Survey. Logistic regression models were conducted to examine characteristics associated with marijuana use behaviors among young adults (aged 15–24). Rates of marijuana use were highest among current smokers and lowest among never smokers. Marijuana use was more prevalent among males, young adults living in rural areas, and increased with age. Young adults who were still in school were more likely to have tried marijuana, although among those who had tried, young adults outside of school were more like to be heavy users. Males and those who first tried marijuana at an earlier age also reported more frequent marijuana use. These findings illustrate remarkably high rates of marijuana use and high co-morbidity of tobacco use among young adult Canadi-ans. These findings suggest that future research should consider whether the increasing popularity of mari-juana use among young adults represents a threat to the continuing decline in tobacco use among this population.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".