Promoting Healthy Choices: The Importance of Differentiating Between Ordinary and High Risk Cannabis Use Among High-School Students
Bibliographic record
Abstract
Education can affect the lives of adolescents by reinforcing healthy choices and promoting a healthy lifestyle. However, difficulties experienced in the school and family environments may interfere with these goals. This may be particularly true for those youth already participating in health-compromising behaviors such as drug use. Of course, patterns of drug use take many forms, and some are more serious than others. Youth using cannabis at more intensive levels have often been overlooked in the literature. This paper, based on 1997 data, addressed this gap by examining the effects of individual and cumulative school and family factors on not only the probability of any cannabis use but also the progression to problem use among 1980 Ontario students. The results suggested that disrupted family structure increased the likelihood of cannabis use in general. However, patterns of problem use were displayed among youth experiencing problems in school and poor family relationships. As anticipated, adolescents experiencing multiple school and family factors were also significantly more likely to engage in cannabis use, and in its more serious form, when controlling for other demographic predictors. The implications for health promotion initiatives in the school are discussed.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".