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Record W4409810229 · doi:10.22158/sssr.v6n2p1

The Empowerment of Drug Users to Combat Fentanyl Crisis Through Organized in a Campout: Based on the Fieldwork in Vancouver

2025· article· en· W4409810229 on OpenAlexaboutno aff

Bibliographic record

VenueStudies in Social Science Research · 2025
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsnot available
Fundersnot available
KeywordsFentanylEmpowermentDrugPsychologyMedicinePolitical scienceAnesthesiaPsychiatryLaw

Abstract

fetched live from OpenAlex

Drug users’ empowerment is critical for their sustainable development, particularly for their survival during the Fentanyl Crisis in which overdose deaths and non-fatal overdoses have increased in recent years across North America. As one of the epicenters, Vancouver has been suffering overdose deaths in the past decade. Simultaneously, Vancouver has a history of empowering drug users to save their lives since the 1990s. Based on the fieldwork in a campout originated by VANDU and REDUN in 2019, this study aims to understand the drug users’ empowerment to construct their strengths, individual competence, and proactive behaviors when they are organized. The active involvement of drug users in their group’s events has enabled them to employ innovative approaches to generate, sustain, and implement alternative methods. Empowering drug users through their organization in policy making and implementing policies to combat the Fentanyl Crisis leads to the evolution of a sustainable society.

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)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.701
Threshold uncertainty score0.594

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0190.005
Scholarly communication0.0030.001
Open science0.0010.004
Research integrity0.0010.003
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 head0.252
GPT teacher head0.612
Teacher spread0.360 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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