Trends in Alcohol and Drug Use among Canadian Adolescents, 1990–2006
Bibliographic record
Abstract
OBJECTIVE: To report trends in rates of drunkenness, alcohol use, and drug use among Canadian adolescents. METHOD: Five national school-based surveys were carried out between 1990 and 2006 as part of the Canadian Health Behaviour in School-aged Children study (n = 4504 to 7010). Students in Grades 6, 8, and 10 were surveyed about the frequency of their drunken episodes and consumption of beer, liquor, and wine. Grade 10 students were also surveyed about their use of drugs. RESULTS: Rates of drunkenness and alcohol use declined slightly from 1990 to 2006, but about one-half of Grade 10 students in 2006 had used cannabis at least once in their lifetime (up from one-third in 1990). Lifetime prevalence rates of using other drug substances were below 10%. CONCLUSIONS: Timely information on alcohol and drug use among adolescents is important to health policy. Declining trends in alcohol misuse is encouraging; however, the proliferation of cannabis use indicates a need for continued surveillance and education about the risks associated with frequent cannabis use.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".