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Record W4240017599 · doi:10.12927/hcq.2016.24480

Peer Support

2016· article· en· W4240017599 on OpenAlexaffabout
Cheryl Forchuk, Michelle Solomon, Tazim Viran

Bibliographic record

VenueHealthcare Quarterly · 2016
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsLawson Health Research InstituteWestern University
Fundersnot available
KeywordsNursingPsychologyMedicineMedical educationBusinessPolitical science

Abstract

fetched live from OpenAlex

The Mental Health Commission of Canada defines peer support as "a supportive relationship between people who have a lived experience in common … in relation to a mental health challenge or illness … related to their own mental health or that of a loved one" (Sunderland et al. 2013: 11). In Ontario, a key resource for peer support is the Ontario Peer Development Initiative (OPDI), which is an umbrella organization of mental health Consumer/Survivor Initiatives (CSIs) and peer support organizations across the province of Ontario. Member organizations are run by and for people with lived experience of a mental health or addiction issue and provide a wide range of services and activities within their communities. The central tenet of member organizations is the common understanding that people can and do recover with the proper supports in place and that peer support is integral to successful recovery. Nationally, Peer Support Accreditation and Certification Canada has recently been established. The relatively new national organization focuses on training and accrediting peer support workers. This paper focuses on a range of diverse peer support groups and CSIs that operate in London and surrounding areas.

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)0.007
metaresearch head score (Gemma)0.057
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.192
Threshold uncertainty score0.641

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.057
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0080.002
Scholarly communication0.0070.004
Open science0.0030.009
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.1920.058

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 head0.190
GPT teacher head0.447
Teacher spread0.257 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations11
Published2016
Admission routes2
Has abstractyes

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