Ecstasy and Drug Consumption Patterns: A Canadian Rave Population Study
Bibliographic record
Abstract
OBJECTIVE: This study investigates the drug consumption patterns of a sample of rave attendees in the city of Montreal, Quebec, and seeks to identify the prevalence of 3,4-methylendioxymethamphetamine (MDMA) and other drug use in this population. METHOD: We administered a self-report questionnaire to 210 respondents. For various licit and illicit substances, participants reported their age of first use, number of lifetime uses, and usage in the previous 30 days. RESULTS: We found a significant rank order for the sequence of first use: 1) alcohol, 2) nicotine, 3) cannabis, 4) LSD, 5) psilocybin, 6) amphetamine, 7) cocaine, 8) MDMA, 9) gamma-hydroxybutyrate (GHB), 10) ephedrine, 11) ketamine. Alcohol and cannabis were the most commonly used substances, both in cumulative number of lifetime uses and in usage in the preceding 30 days. MDMA and amphetamine were also notable as the next 2 most popular drugs for use in the preceding 30 days and in terms of those who had tried the drugs at least once. We identified a progressive rank order of experimentation, with early alcohol or cannabis use (or both) associated with the early use of all other drugs tried by more than 25% of the sample. We found MDMA and amphetamine use to be prevalent, as was general experimentation with all drugs studied, other than heroin. CONCLUSION: Drug consumption levels were substantial in this "rave" population, particularly with respect to recent use of MDMA, amphetamine, cannabis, and alcohol. Results also indicate that the sequence of drug experimentation in this population follows an identifiable pattern.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".