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Record W4309589877 · doi:10.7870/cjcmh-2022-015

Peer Counsellor Training for Sex Workers: A Pilot Program in Lekwungen Territory (Victoria, BC)

2022· article· en· W4309589877 on OpenAlexaffvenue
Allison Reeves, Kathryn J. Saunders, Rachel Phillips

Bibliographic record

VenueCanadian Journal of Community Mental Health · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsMental healthMainstreamPsychologyMedical educationStigma (botany)Sex workSocial workNursingMedicinePsychiatryFamily medicinePolitical science

Abstract

fetched live from OpenAlex

Sex workers face significant stigma when accessing mental health services, due to the history of criminalization of sex work and the resulting negative biases in the healthcare sector. Peers Victoria Resources Society is a sex worker advocacy organization who partnered with the researchers to develop and implement a pilot program on peer-counsellor skills development for sex workers incorporating trauma informed practice. The course sought to build on leadership, capacity and strengthen solidarity while acknowledging societal stigma, in hopes that this pilot could result in supplementary care to mainstream mental health services for this underserved community. Interviews were conducted with eight participants prior to and following the 10-week course. Participants reported increased competency in basic counselling skills such as reflective listening, and all noted the applicability of these skills in their personal and working lives. Suggestions were made to scaffold future course content to manage both academic and emotional learning.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.843
Threshold uncertainty score0.312

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.001
Scholarly communication0.0010.000
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.095
GPT teacher head0.377
Teacher spread0.282 · 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

Citations1
Published2022
Admission routes2
Has abstractyes

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