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Record W2165894098 · doi:10.1503/cmaj.1031928

Displacement of Canada's largest public illicit drug market in response to a police crackdown

2004· article· en· W2165894098 on OpenAlexafffundvenueabout
Evan Wood

Bibliographic record

VenueCanadian Medical Association Journal · 2004
Typearticle
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsUniversity of British Columbia
FundersNational Institute on Drug AbuseCanadian Institutes of Health ResearchNational Institutes of HealthMichael Smith Health Research BC
KeywordsHeroinMedicineIllicit drugMethadoneLaw enforcementPublic healthDemographyEnvironmental healthDrugPsychiatryPolitical scienceLaw

Abstract

fetched live from OpenAlex

BACKGROUND: Law enforcement is often used in an effort to reduce the social, community and health-related harms of illicit drug use by injection drug users (IDUs). There are, however, few data on the benefits of such enforcement or on the potential harms. A large-scale police "crackdown" to control illicit drug use in Vancouver's Downtown Eastside provided us with an opportunity to evaluate the effect. METHODS: As part of our ongoing prospective cohort study of IDUs in Vancouver, we examined data collected from 244 IDUs in the 3 months before the police crackdown and from 142 IDUs in the 3 months after the start of the crackdown, on Apr. 7, 2003. All study subjects were active drug users. We also examined external data on needle exchanges and syringe disposal. RESULTS: The 2 groups of IDUs were statistically similar: they were mainly young (mean age 39 years) and male (63%), and they had injected illicit drugs for 13 years on average. Ethnic background and the proportion homeless were also similar. There were no statistically significant reported differences (all p > 0.1) in the street price of heroin, cocaine or "crack" in the 2 periods. In the 3-month periods before and after the crackdown, respectively, the rates of daily heroin injection were 27.9% and 26.8%, daily cocaine injection 28.7% and 27.5%, and daily crack use 59.4% and 60.6% (all p > 0.1). The proportions of study subjects receiving methadone treatment, 41.0% and 44.4% (p = 0.516), did not differ. However, the proportions reporting a change in where drugs were used, 22.5% and 33.8% (p < 0.05), and the proportions reporting a change in the neighbourhood of use because of police presence, 18.1% and 26.8% (p < 0.05), increased significantly. Needle-exchange data confirmed that the community levels of drug use were unchanged. Disposal statistics demonstrated that the monthly average number of used syringes found on the streets outside the traditional area of drug use increased from 784 in the 3 months before Apr. 1 to 1253 in the subsequent 3 months (p = 0.002) and the monthly average number of used syringes found in public boxes for the safe disposal of syringes decreased from 865 to 502 (p = 0.018). INTERPRETATION: The effort to control illicit drug use did not alter the price of drugs or the frequency of use, nor did it encourage enrollment in methadone treatment programs. Several measures indicated displacement of injection drug use from the area of the crackdown into adjacent areas of the city, which has implications for both recruitment of new initiates into injection drug use and HIV prevention efforts.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.030
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.001
Scholarly communication0.0020.000
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.011
GPT teacher head0.277
Teacher spread0.267 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations191
Published2004
Admission routes4
Has abstractyes

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