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Record W2400460939 · doi:10.1186/s12889-016-3136-4

Peer engagement in harm reduction strategies and services: a critical case study and evaluation framework from British Columbia, Canada

2016· article· en· W2400460939 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueBMC Public Health · 2016
Typearticle
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsUniversity of British ColumbiaPositive Living Society of British ColumbiaBC Centre for Disease Control
Fundersnot available
KeywordsBiostatisticsMedicineHarm reductionPublic healthPeer reviewHealth services researchHarmEpidemiologyEnvironmental healthFamily medicineNursingLawPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Engaging people with drug use experience, or 'peers,' in decision-making helps to ensure harm reduction services reflect current need. There is little published on the implementation, evaluation, and effectiveness of meaningful peer engagement. This paper aims to describe and evaluate peer engagement in British Columbia from 2010-2014. METHODS: A process evaluation framework specific to peer engagement was developed and used to assess progress made, lessons learned, and future opportunities under four domains: supportive environment, equitable participation, capacity building and empowerment, and improved programming and policy. The evaluation was conducted by reviewing primary and secondary qualitative data including focus groups, formal documents, and meeting minutes. RESULTS: Peer engagement was an iterative process that increased and improved over time as a consequence of reflexive learning. Practical ways to develop trust, redress power imbalances, and improve relationships were crosscutting themes. Lack of support, coordination, and building on existing capacity were factors that could undermine peer engagement. Peers involved across the province reviewed and provided feedback on these results. CONCLUSION: Recommendations from this evaluation can be applied to other peer engagement initiatives in decision-making settings to improve relationships between peers and professionals and to ensure programs and policies are relevant and equitable.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.439
Threshold uncertainty score0.862

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.112
GPT teacher head0.409
Teacher spread0.297 · 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