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Record W2928227103 · doi:10.1080/09638237.2019.1581338

Choice and personal recovery for people with serious mental illness living in supported housing

2019· article· en· W2928227103 on OpenAlexafffund
Myra Piat, Kimberly Seida, Deborah K. Padgett

Bibliographic record

VenueJournal of Mental Health · 2019
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsDouglas CollegeDouglas Mental Health University InstituteMcGill University
FundersCanadian Institutes of Health Research
KeywordsMental illnessMental healthContext (archaeology)PsychologyRelevance (law)Scope (computer science)Qualitative researchPublic housingSocial psychologyPsychiatrySociologyEconomic growthEconomics

Abstract

fetched live from OpenAlex

Background: The relationship between personal choice and mental health recovery in the context of supported housing has not been explored.Aims: To gain an understanding of how choice facilitates recovery processes in supported housing environments for those with serious mental illness (SMI).Method: Qualitative in-depth interviews were conducted with 24 tenants with SMI living in supported housing.Results: Choice while living in supported housing was a large contributor to wellbeing and mental health recovery. Tenants valued three domains of choice: (1) choosing to be responsible for one’s life, (2) choosing how to organize one’s social life and (3) choices that make them feel “at home”.Conclusion: This is one of the first studies on choice and recovery for persons who have transitioned to supported housing. Findings reveal the need for research to move beyond focusing on choice of housing (e.g. housing type) and explore the scope and relevance of choice in housing.

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)0.001
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 score0.223
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.024
GPT teacher head0.383
Teacher spread0.360 · 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

Citations36
Published2019
Admission routes2
Has abstractyes

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