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Record W4410164209 · doi:10.1080/02673037.2025.2498379

Residents’ perception of the quality and impact of different models of permanent supportive housing

2025· article· en· W4410164209 on OpenAlexafffundabout
Marie‐Josée Fleury, Armelle Imboua, Xiangfei Meng

Bibliographic record

VenueHousing Studies · 2025
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsMcGill UniversityDouglas Mental Health University Institute
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPerceptionQuality (philosophy)BusinessPsychologyPublic economicsEconomicsEpistemology

Abstract

fetched live from OpenAlex

This study explored the similarities and differences that residents perceived regarding the quality of the permanent supportive housing (PSH) model they lived in, housing features and support, other services received, residential stability, community integration, and quality of life. Based on a previous study (T1, N = 308), 60 Quebec (Canada) PSH residents were randomly recruited in 2023 (T2) for this mixed-methods study. Compared to other models, scattered-site PSH housed more women and younger residents with better perceived mental/physical health conditions, and at T2 more improved social conditions; community PSH offered more continuous support and a safer environment, while social PSH (a hybrid of the other two) included residents with more long-term residential stability. Scattered-site and social PSH may be more appropriate for individuals with greater autonomy, and community PSH for those with continuous needs. For the former, a safe living environment and access to the job market or to community involvement may be prioritized, while the latter may benefit from greater autonomy.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.723

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.163
GPT teacher head0.511
Teacher spread0.348 · 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 teacher head, 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

Citations0
Published2025
Admission routes3
Has abstractyes

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