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Record W1981635446 · doi:10.1007/s10464-014-9632-8

Comparing the Characteristics of Homeless Adults in Poland and the United States

2014· article· en· W1981635446 on OpenAlexaff
Paul A. Toro, Karen L. Hobden, Kathleen Wyszacki Durham, Marta Oko‐Riebau, Anna Bokszczanin

Bibliographic record

VenueAmerican Journal of Community Psychology · 2014
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsHealth psychologyMental healthComparabilitySubstance abusePublic healthPsychologySubstance usePsychiatryClinical psychologyDemographyMedicineGerontology

Abstract

fetched live from OpenAlex

This study compared the characteristics of probability samples of homeless adults in Poland (N = 200 from two cities) and the United States (N = 219 from one city), using measures with established reliability and validity in homeless populations. The same measures were used across nations and a systemic translation procedure assured comparability of measurement. The two samples were similar on some measures: In both nations, most homeless adults were male, many reported having dependent children and experiencing out-of-home placements when they themselves were children, and high levels of physical health problems were observed. Significant national differences were also found: Those in Poland were older, had been homeless for longer, showed lower rates on all psychiatric diagnoses assessed (including severe mental and substance abuse disorders), reported less contact with family and supportive network members, were less satisfied when they sought support from their networks, and reported fewer recent stressful life events and fewer risky sexual behaviors. Culturally-informed interpretations of these findings and their implications are presented.

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)0.003
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 score0.057
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.049
GPT teacher head0.420
Teacher spread0.371 · 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

Citations22
Published2014
Admission routes1
Has abstractyes

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