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Record W4403777057 · doi:10.1177/00914509241293394

“Everyone Does Cocaine”: The Impact of Normalization on Practices of Club Drug Use and Risk Management

2024· article· en· W4403777057 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueContemporary Drug Problems · 2024
Typearticle
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsTrent University
FundersSocial Sciences and Humanities Research Council
KeywordsNormalization (sociology)DrugClubJournal clubPsychologyMedicineBusinessPsychiatrySociologySocial scienceMedical education

Abstract

fetched live from OpenAlex

Background While many have argued that recreational drug use is becoming increasingly normalized within youth culture, little has been done to explore what this means for risk management. Methods Drawing on 2 years of ethnographic research with people who use club drugs in the Toronto Electronic Dance Music scene, this study explores how normalization impacts risk-taking and risk management practices of club drug use. Results It finds that the relationship is complex, as normalization both facilitates and hinders the adoption of risk management practices. The nuances of this relationship are explored by focusing on three key themes: expectation of use, moderation of use, and sharing of risk information and advice. Conclusion The findings are interpreted with reference to Rhodes’ “risk environment” framework and with particular attention to the need for harm reduction interventions that consider how risk behaviors are shaped by broader social and cultural contexts.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.158
Threshold uncertainty score0.585

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.054
GPT teacher head0.347
Teacher spread0.293 · 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