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Record W4396688200 · doi:10.1002/ajcp.12754

The role of housing stability in predicting social capital: Exploring social support and psychological integration as mediators for individuals with histories of homelessness and vulnerable housing

2024· article· en· W4396688200 on OpenAlexaffabout
Ayda Agha, Stephen W. Hwang, Anita Palepu, Tim Aubry

Bibliographic record

VenueAmerican Journal of Community Psychology · 2024
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsCentre for Advancing Health OutcomesUniversity of British ColumbiaSt. Michael's HospitalUniversity of Ottawa
Fundersnot available
KeywordsHealth psychologySocial capitalPsychologyPublic housingSocial supportSupportive housingSocial psychologyPublic healthSociologyCriminologyEconomic growthPsychiatryMedicineEconomicsSocial scienceNursing

Abstract

fetched live from OpenAlex

Social capital is a collective asset important for individual and population well-being. Individuals who experience homelessness may face barriers in accessing social capital due to health challenges, small social networks, and social exclusion. Data from a 4-year longitudinal study was used to determine if housing stability predicted greater social capital and if this relationship was mediated by social support and psychological integration for a sample of 855 homeless and vulnerably housed participants living in three Canadian cities. Findings showed that housing stability was not associated with trust and linking social capital. However, higher levels of social support and psychological integration had a mediating effect on the association between housing stability and trust and linking social capital. These findings highlight the importance of social support and psychological integration as means of promoting social capital for people who experience homelessness and vulnerable housing. Social interventions for housed individuals with histories of homelessness may be an avenue to foster greater social capital by building relationships with neighbors and connections to community resources and activities.

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)0.004
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.272
Threshold uncertainty score0.844

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.100
GPT teacher head0.435
Teacher spread0.335 · 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

Citations11
Published2024
Admission routes2
Has abstractyes

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