The role of economic and cultural status as risk indicators for alcohol and marijuana use among adolescents
Bibliographic record
Abstract
INTRODUCTION: A number of reports suggest that Aboriginal cultural status is a major risk indicator for drug and alcohol use. The primary purpose of the present paper was to determine whether Aboriginal cultural status is independently associated with risk behaviours, such as marijuana use and alcohol abuse, among youth after multivariate adjustment for other factors, such as socioeconomic status. METHODS: Every student between grades 5 and 8 in Saskatoon, Saskatchewan, was asked to complete a questionnaire in February 2007. Logistic regression was used to determine the independent risk indicators associated with alcohol abuse and marijuana use. RESULTS: Four thousand ninety-three youth participated in the school health survey. At the cross-tabulation level, cultural status and neighbourhood income were both strongly associated with alcohol and marijuana use. After multivariate adjustment, the association between Aboriginal cultural status and alcohol abuse was not statistically significant (crude OR=3.52 to adjusted OR=0.80). For marijuana use, the association was significantly reduced (crude OR=9.91 to adjusted OR=2.79). After controlling for all other variables, results showed that low-income youth were 103% more likely to get drunk at least once and were 163% more likely to have tried marijuana at least once. CONCLUSION: To be more successful, future policies directed toward reducing risk behaviours among youth should consider neighbourhood income characteristics.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".