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Record W2312969199 · doi:10.7870/cjcmh-2014-034

Peer Supportive Housing for Consumers of Housing First Who Experience Ongoing Housing Instability

2014· article· en· W2312969199 on OpenAlexafffundvenueabout
Stéphanie Yamin, Tim Aubry, Jennifer S. Volk, Jonathan Jetté, Jimmy Bourque, Susan Crouse

Bibliographic record

VenueCanadian Journal of Community Mental Health · 2014
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsMoncton HospitalUniversité de MonctonUniversity of Ottawa
FundersHealth CanadaMental Health Commission
KeywordsHousing FirstSupportive housingPublic housingAffordable housingPeer supportBusinessPsychologyMental illnessPublic relationsMental healthEngineeringPsychiatryPolitical scienceCivil engineering

Abstract

fetched live from OpenAlex

Housing First (HF) effectively houses the majority of homeless individuals suffering from mental illness; however, a small subset continues to struggle with unstable housing. This paper describes a supportive housing pilot program developed at the Moncton site of the At Home / Chez Soi demonstration project for HF participants who have experienced difficulty achieving housing stability while receiving HF services. Specifically, Peer Supportive Housing (PSH) was created for participants demonstrating ongoing unstable housing in the HF program. Results from structured interviews with five program staff and nine tenants of PSH describe the successes, challenges, and perceived outcomes of the early implementation of the program. PSH can supplement HF, and may help to meet the needs of some tenants who are unable to achieve stable housing after a trial of receiving HF services.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.106
GPT teacher head0.431
Teacher spread0.325 · 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 designObservational
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

Citations10
Published2014
Admission routes4
Has abstractyes

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