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Record W2469509310 · doi:10.1002/ajcp.12066

Individual, Housing, and Neighborhood Predictors of Psychological Integration Among Vulnerably Housed and Homeless Individuals

2016· article· en· W2469509310 on OpenAlexafffundabout
John Ecker, Tim Aubry

Bibliographic record

VenueAmerican Journal of Community Psychology · 2016
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of Ottawa
FundersSocial Sciences and Humanities Research Council of CanadaCanadian Institutes of Health Research
KeywordsHealth psychologyPsychologyFeelingMultilevel modelSocial supportLongitudinal studyGerontologyPublic healthPopulationSupportive housingClinical psychologyMedicineEnvironmental healthPsychiatrySocial psychologyNursing

Abstract

fetched live from OpenAlex

The current longitudinal study evaluated the individual, housing, and neighborhood characteristics predictive of feeling psychologically integrated within one's neighborhood among a population of homeless and vulnerably housed individuals. Participants were recruited at homeless shelters, meal programs, and rooming houses in Ottawa, Canada and participated in three in-person interviews, each approximately 1 year apart. Prospective and cross-sectional predictors of psychological integration at Follow-up 1 and Follow-up 2 were examined. There were 397 participants at baseline, 341 at Follow-up 1 and 320 at Follow-up 2. A hierarchical multiple regression uncovered several significant predictors of psychological integration. The most salient and common predictors were being older, having greater social support, living in high quality housing, and residing in a neighborhood with a positive impact. Implications for service provision and policy advancements are discussed.

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)0.002
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 score0.149
Threshold uncertainty score0.649

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
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 head0.068
GPT teacher head0.436
Teacher spread0.367 · 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

Citations28
Published2016
Admission routes3
Has abstractyes

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