Development of the REACH (Real Education About Cannabis and Health) Program for Canadian Youth
Bibliographic record
Abstract
BACKGROUND: Because cannabis use in children can have negative consequences, the recent legalization of recreational cannabis for adults in Canada creates an urgent need for youth education. METHOD: A multidisciplinary clinical rotation was developed wherein nursing and pharmacy students collaborated with youth (grades 7 through 10) to construct an educational program about cannabis. Four schools participated, representing a variety of socioeconomic demographics. Feedback was solicited from students and stakeholders. The purpose of this project was to create REACH (Real Education About Cannabis and Health), a toolkit and curriculum resource that includes lesson plans for teachers covering the science of cannabis, social science implications, peer pressure, decision making and harm reduction, videos featuring youth testimonials, and supplemental resources. RESULTS: Preliminary feedback suggests the materials are engaging and informative. CONCLUSION: A collaboration of health science students with youth in schools resulted in an authentic and relatable educational program about cannabis. Future studies will evaluate REACH's effectiveness in seventh- and ninth-grade students. [J Nurs Educ. 2020;59(8):465-469.].
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".