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Record W2900758024 · doi:10.1177/1524839918816328

Participant-Driven Health Education Workshops With Men Transitioning From Prison to Community

2018· article· en· W2900758024 on OpenAlexafffundabout
Katherine McLeod, Cara Bergen, Kate Roth, Catherine Latimer, Debra Hanberg, Blake Stitilis, Jane A. Buxton, Lynn Fels, John L. Oliffe, Nicole Myers, Carl Leggo, Ruth Elwood Martin

Bibliographic record

VenueHealth Promotion Practice · 2018
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsSimon Fraser UniversityUniversity of British Columbia
FundersFace The World FoundationMichael Smith Health Research BCVancouver Foundation
KeywordsPrisonCommunity-based participatory researchParticipatory action researchFocus groupMedical educationCitizen journalismCommunity healthPsychologyNursingGerontologyMedicinePolitical sciencePublic healthSociologyCriminology

Abstract

fetched live from OpenAlex

As part of a participatory health research project seeking to support men in achieving their health goals during the transition from prison to community, a workshop program was developed and piloted in a Community Residential Facility in British Columbia, Canada. The pilot program was evaluated through feedback surveys at each of the 16 workshops and a focus group interview at the end of the program. Workshops were highly valued by participants and seen as a means for (1) building skills relevant to their health and wellness, (2) working toward changing attitudes and behaviors adopted in prison, and (3) helping others and accepting help from others. Similar programs may be an effective support for men working to achieve their health goals during other transitions (e.g., bereavement, cancer patients, returning soldiers, and veterans).

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)0.014
metaresearch head score (Gemma)0.010
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 score0.014
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0080.002
Scholarly communication0.0020.001
Open science0.0020.005
Research integrity0.0020.002
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 head0.149
GPT teacher head0.510
Teacher spread0.361 · 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

Citations4
Published2018
Admission routes3
Has abstractyes

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