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Record W4386615781 · doi:10.5206/ijoh.2023.3.15678

A Grounded Theory of Provider Perspectives Regarding Resident Moves from Permanent Supportive Housing

2023· article· en· W4386615781 on OpenAlexvenueno aff
Jordan M. Goodwin, Emmy Tiderington

Bibliographic record

VenueInternational Journal on Homelessness · 2023
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsGrounded theoryMindsetService providerGatekeepingAutonomyEmpowermentBusinessPerceptionHousing FirstSupportive housingPublic relationsQualitative researchNursingMarketingPsychologyEconomic growthSociologyPolitical scienceMedicineMental healthEconomics

Abstract

fetched live from OpenAlex

To address the ongoing supply-demand gap for permanent supportive housing (PSH), Moving On initiatives (MOIs) provide linkage to affordable housing without embedded support services and rental subsidies, as well as short-term transitional case management to support transitions to independent housing. PSH providers mediate outcomes for individuals moving on from PSH by providing appropriate supports and assistance. Yet, little is known about how providers view these moves. This study explores how providers perceive moves from PSH. Individual interviews were completed with PSH providers from seven U.S. agencies. Data was analyzed via a modified grounded theory approach. The data show that organizational support and prior experience with moving on shape providers’ perceptions of resident capacity. These perceptions were associated with gatekeeping and recovery-oriented approaches, which informed providers’ self-perceived role as following or leading residents towards moving on. System-level support and pressure to adopt a moving on mindset may lead more providers to promote independence and autonomy among individuals with histories of homelessness.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.144
Threshold uncertainty score0.766

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.058
GPT teacher head0.409
Teacher spread0.350 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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