Are School Substance Use Policy Violation Disciplinary Consequences Associated with Student Engagement in Cannabis?
Bibliographic record
Abstract
Schools are increasingly concerned about student cannabis use with the recent legalization in Canada; however, little is known about how to effectively intervene when students violate school substance use policies. The purpose of this study is to assess the disciplinary approaches present in secondary schools prior to cannabis legalization and examine associations with youth cannabis use. This study used Year 6 (2017/2018) data from the COMPASS (Cannabis use, Obesity, Mental Health, Physical Activity, Alcohol use, Smoking, Sedentary behavior) study including 66,434 students in grades 9 through 12 and the 122 secondary schools they attend in British Columbia, Alberta, Ontario, and Quebec. Student questionnaires assessed youth cannabis use and school administrator surveys assessed potential use of 14 cannabis use policy violation disciplinary consequences through a ("check all that apply") question. Regression models tested the association between school disciplinary approaches and student cannabis use with student- (grade, sex, ethnicity, tobacco use, binge drinking) and school-level covariates (province, school area household median income). For first-offence violations of school cannabis policies, the vast majority of schools selected confiscating the product (93%), informing parents (93%), alerting police (80%), and suspending students from school (85%), among their disciplinary response options. Few schools indicated requiring students to help around the school (5%), issuing a fine (7%), or assigning additional class work (8%) as potential consequences. The mean number of total first-offence consequences selected by schools was 7.23 (SD = 2.14). Overall, 92% of schools reported always using a progressive disciplinary approach in which sanctions get stronger with subsequent violations. Students were less likely to report current cannabis use if they attended schools that indicated assigning additional class work (OR 0.57, 95% CI (0.38, 0.84)) or alerting the police (OR 0.81, 95% CI (0.67, 0.98)) among their potential first-offence consequences, or reported always using the progressive discipline approach (OR 0.77, 95% CI (0.62, 0.96)) for subsequent cannabis policy violations. In conclusion, results reveal the school disciplinary context in regard to cannabis policy violations in the year immediately preceding legalization. Various consequences for cannabis policy violations were being used by schools, yet negligible association resulted between the type of first-offence consequences included in a school's range of disciplinary approaches and student cannabis use.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".