Patterns of Youth Participation in Cannabis Cultivation
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
The current study examines the patterns of youth participation in cannabis cultivation by developing a typology among a sample of young offenders (n=175) in a rural region of Quebec, Canada known for its extensive outdoor cultivation industry. A hierarchical cluster analysis approach is used to group participants on various dimensions: motivation, substance use, delinquency and type of participation in cannabis cultivation. We also explore the role that criminal networks have in structuring the nature of youth involvement in the cultivation industry. Two general categories of participants emerged: participants for which cultivation is mainly a money generating activity (Entrepreneurs and Generalists), and participants who grow for personal use and intangible rewards (Hobbyists). Further, we found another group, the “helpers”, who qualify as “participants” to the cultivation industry, but not as “growers” per se. For generalists, participation to the cultivation industry is found among a portfolio of other crimes, while entrepreneurs tend to specialize in cultivation and are rewarded by achieving a higher level of success. Our results also suggest a correlation between the intensity of involvement in cultivation and the size of a youth's criminal network.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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