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Record W2016216129 · doi:10.1080/01609513.2010.503385

Evaluating Canada's Drug Prevention Strategy and Creating a Meaningful Dialogue with Urban Aboriginal Youth

2010· article· en· W2016216129 on OpenAlexaffabout
Amar Ghelani

Bibliographic record

VenueSocial Work With Groups · 2010
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDrug preventionPsychologySociologyCriminologyDevelopmental psychologySubstance abusePsychotherapist

Abstract

fetched live from OpenAlex

This article describes some of the risks and challenges faced by Aboriginal youth living in Canadian cities. It evaluates four current drug prevention/education programs for this group and other at-risk youth. The lessons learned from these strategies lead to a proposal for a reflective education approach directed toward opening meaningful dialogue about drugs and alcohol with urban Aboriginal youths in group settings. The objectives of the approach are to create an open dialogue with youths, enhance problem-solving skills, minimize harm, and initiate a process of reflection about the role of drugs in the lives of young people. The goal is for the proposed approach to be implemented in various group contexts, including classrooms, workshops, talking circles, treatment centers and sports clubs. The article also explores the practice and policy dimensions of prevention-focused social work with Aboriginal youth.

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)0.016
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.915
Threshold uncertainty score0.617

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0200.003
Scholarly communication0.0050.002
Open science0.0020.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.022
GPT teacher head0.299
Teacher spread0.277 · 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 designQualitative
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
Published2010
Admission routes2
Has abstractyes

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