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Record W129801663

Diversity and homelessness: minorities and psychiatric survivors.

2007· article· en· W129801663 on OpenAlexaffabout
Cheryl Forchuk, Elsabeth Jensen, Rick Csiernik, Carolyn Gorlick, Susan L. Ray, Hélène Berman, Pamela McKane, Libbey Joplin

Bibliographic record

VenuePubMed · 2007
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsWestern University
Fundersnot available
KeywordsDiversity (politics)PovertySexual orientationMental illnessMental healthPsychologyParticipatory action researchSexual minoritySociologyPolitical sciencePsychiatrySocial psychology
DOInot available

Abstract

fetched live from OpenAlex

This study explores the intersecting vulnerabilities in individuals who are homeless and have psychiatric challenges.Psychiatric survivors are often perceived as a homogeneous group with similar needs.However, survivors with further minority status are likely to have additional concerns and needs that may not be met by the current systems of care.People further marginalized by visible/cultural minority-group status, sexual orientation, and/or disabilities are being studied through this line of research.While possessing any of these vulnerabilities can increase the risk for poverty and homelessness, the interaction among them is poorly understood, particularly in relation to housing and homelessness. GoalsA key objective of the Homelessness and Diversity Issues in Canada initiative is to support policy-relevant research on homelessness in Canada as it relates to diversity.The project directly addresses this objective by examining the interplay between two issues related to diversity (mental illness and membership in a visible or cultural minority group) and homelessness.Students will have the opportunity to participate in research related to this understudied area.The participatory and interdisciplinary approach promotes the sharing of knowledge among researchers and the users of research. MethodsThe project has three stages: 1. Secondary analysis of data collected through the Community University Research Alliance on Housing and Mental Health.This data set includes interviews with 300 individuals conducted in 2004 and again in 2005.Of this sample, more than a quarter of respondents were interviewed in shelters.The data will be explored for racial/ ethnic differences.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.051
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0020.002
Open science0.0000.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.046
GPT teacher head0.320
Teacher spread0.274 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2007
Admission routes2
Has abstractyes

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