Does Medical Presence Decrease the Perceived Risk of Substance-Related Harm at Music Festivals?
Bibliographic record
Abstract
Introduction: The use of recreational substances is a contributor to the risk of morbidity and mortality at music festivals. One of the aims of onsite medical services is to mitigate substance-related harms. It is known that attendees’ perceptions of risk can shape their planned substance use; however, it is unclear how attendees perceive the presence of onsite medical services in evaluating the risk associated with substance use at music festivals. Methods: A questionnaire was administered to a random sample of attendees entering a multi-day electronic dance music festival. Results: There were 630 attendees approached and 587 attendees completed the 19 item questionnaire. Many confirmed their intent to use alcohol (48%, n=280), cannabis (78%, n=453), and recreational substances other than alcohol and cannabis (93%, n=541) while attending the festival. The majority (60%, n=343) stated they would still have attended the event if there were no onsite medical services available. Some attendees agreed that the absence of medical services would have reduced their intended use of alcohol (30%, n=174) and recreational substances other than alcohol and cannabis (46%, n=266). Discussion: In the context of a music festival, plans for recreational substance use appear to be substantially altered by attendees’ knowledge about the presence or absence of onsite medical services. This contradicts our initial hypothesis that medical services are independent of planned substance use and serve solely to reduce any associated harms. Additional exploration and characterization of this phenomenon at various events would further clarify the understanding of perceived risks surrounding substance use and the presence of onsite medical services.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 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".