Cannabis Use in British Columbia: patterns of use, perceptions, and public opinion as assessed in the 2004 Canadian Addiction Survey
Bibliographic record
Abstract
Overview: This bulletin examines aspects of cannabis use in BC compared with the rest of Canada, with special attention paid to potentially risky patterns of use1. Cannabis use is more widespread in BC than in the rest of Canada, and its illegal production contributes significantly to the local economy. Analysis of the 2004 Canadian Addiction Survey (CAS) suggests that 1.84 million persons in BC have tried cannabis at least once. Compared with other Canadians, significantly fewer BC respondents said they believed cannabis use should be illegal (42% versus 49%), while significantly more stated they: • had ever used cannabis in the past—53% in BC versus 44% elsewhere • experienced access to be ‘very easy’—65% in BC versus 44% elsewhere • believed both occasional and regular cannabis use to be harm–free. There was mixed evidence suggesting that this situation has led to increased levels of risky use and harm. Age of first use (18.6 years versus 18.9 years elsewhere) and rates of daily use (3% in BC and elsewhere), dependence, and of driving under the influence of cannabis were not significantly different. However, significantly more BC users reported trying to control their use, having friends express concern about their use, having combined their cannabis with alcohol, and were classified as “moderate risk users” on the WHO ASSIST scale. There was also less concern about alcohol in BC than in the rest of Canada, but more concern about heroin and methamphetamine. In general, cannabis users were more likely to be young, male, and have higher education than non-users. Overall, these results suggest that greater availability, prevalence, and acceptability of cannabis in BC than in the rest of Canada has resulted in modest increases in potentially hazardous use. It would appear cannabis is regarded in BC in a similar way to alcohol, with many using it in a relatively low-risk manner and many still underestimating its risks.
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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 | 0.004 |
| 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".