Prevalence and Predictors of “Heavy” Marijuana Use in a Canadian Youth Sample
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this investigation, secondary analyses were performed on an extensive database for 473 biological and 128 adoptive families. These data, which were gathered as part of the Vancouver Family Survey, were used to examine the prevalence and predictors of "heavy" marijuana use in a Canadian youth sample aged 14-25. Results in this study showed that 12.6% of the sample reported using marijuana once a week or more. These respondents were categorized as "heavy" marijuana users. Higher levels of life problems were associated with this use pattern. Results from a series of regression analyses suggested that the family, personality, and peer domains all contributed significantly in predicting "heavy" marijuana use. Father's alcoholism and peer illicit drug use had direct relationships with heavy marijuana use in this final model. A possible mediated pathway was also suggested with the Addiction Prone Personality influencing use through its relationship with heavier peer drug use.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it