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Record W2032900822 · doi:10.1080/15332640.2011.547791

Ethno-Cultural Differences in the Use of Alcohol and Other Drugs: Evidence from the Vancouver Youth Drug Reporting System

2011· article· en· W2032900822 on OpenAlexaffabout
Cameron Duff, Ajay Puri, Clifton Chow

Bibliographic record

VenueJournal of Ethnicity in Substance Abuse · 2011
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsUniversity of British ColumbiaProvidence Health CareVancouver Coastal Health
Fundersnot available
KeywordsAlcoholDrugMedicineEthnic groupDrug preventionPeer groupClinical psychologyPsychiatryPsychologySubstance abuseDevelopmental psychologyPolitical science

Abstract

fetched live from OpenAlex

This article reports on ethno-cultural differences in the use of alcohol and other drugs by using data derived from the Vancouver Youth Drug Reporting System. Data were collected between May and August 2006 among a sample of 514 youth aged 16 to 25. Statistically significant ethno-cultural differences were reported for "lifetime" alcohol and other drugs prevalence; alcohol and other drugs experience in the peer group; parental attitudes; and in the assessment of alcohol and other drugs prevention strategies. White and Aboriginal youth reported significantly higher rates of personal and peer group alcohol and other drugs use than other groups, whereas Chinese youth reported the lowest rates.The implications of these findings for alcohol and other drug prevention efforts are briefly discussed.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.125
Threshold uncertainty score0.975

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.271
GPT teacher head0.334
Teacher spread0.063 · 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.

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

Citations14
Published2011
Admission routes2
Has abstractyes

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