MétaCan
Menu
Back to cohort
Record W2418543796

Harm reduction in the rave community.

2000· article· en· W2418543796 on OpenAlexaboutno aff
K Henricksen

Bibliographic record

VenuePubMed · 2000
Typearticle
Languageen
FieldPsychology
TopicDiversity and Impact of Dance
Canadian institutionsnot available
Fundersnot available
KeywordsHarm reductionEcstasyHarmPsychologyEveningPerceptionCriminologySocial psychologyAdvertisingMedicinePsychiatryHuman immunodeficiency virus (HIV)BusinessFamily medicine
DOInot available

Abstract

fetched live from OpenAlex

Raves are exclusive, private parties, usually held in the late evening at undisclosed locations, where people, referred to as ravers, come together to experience sensory art, dance, and music. Ravers can also use Club Drugs, such as speed, Special K and ecstasy. The accessibility of drugs is regarded as safe among the rave community because of the understanding between participants to use them responsibly for heightened perception. However, inexperienced ravers may not follow the same code, and drug use leads them to risky behaviors and potential overdose. Many of the drugs are illegal and may be mislabeled, which can cause adverse reactions and death. DanceSafe and the Toronto Raver Information Project were formed by ravers to address safety perception problems with these parties. The groups distribute factual information on drugs and risks for contracting HIV through unprotected sex, and also dispense condoms. Additionally, the DanceSafe booth provides sober volunteers who can assist and counsel ravers who are having trouble during the party and beyond. The intention of these groups is for harm reduction and support for ravers by ravers who present no threat or bias.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.915
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.067
GPT teacher head0.281
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2000
Admission routes1
Has abstractyes

Explore more

Same venuePubMedSame topicDiversity and Impact of DanceFrench-language works237,207