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Record W1987763158 · doi:10.1080/09687599.2014.902359

Using a capabilities approach to understand poverty and social exclusion of psychiatric survivors

2014· article· en· W1987763158 on OpenAlexaffabout
Sarah Benbow, Abraham Rudnick, Cheryl Forchuk, Betty Edwards

Bibliographic record

VenueDisability & Society · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsLawson Health Research InstituteUniversity of VictoriaUniversity of British ColumbiaVoiceAge (Canada)Western University
FundersWorld Health Organization
KeywordsPovertySocial exclusionStigma (botany)Thematic analysisSocial deprivationPsychologySociologySocial justiceSocial stigmaCriminologyPsychiatryPolitical scienceMedicineQualitative researchSocial science

Abstract

fetched live from OpenAlex

The purpose of this project is to better understand poverty and social exclusion of psychiatric survivors using a capabilities approach to social justice as part of a larger mixed-methods longitudinal study (N=380) in Ontario, Canada. Using thematic coding, four themes emerged: poverty, ‘You just try to survive’; stigma, ‘People treat you like trash’; belonging, ‘You feel like you don’t belong’; and shared concern and advocacy, ‘Everyone deserves housing’. This analysis provides a deeper understanding of poverty and other social determinants of experiences of psychiatric survivors, including the synergism of poverty and social exclusion.

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)0.007
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.318
Threshold uncertainty score0.633

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0050.003
Science and technology studies0.0120.010
Scholarly communication0.0050.005
Open science0.0010.011
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.059
GPT teacher head0.341
Teacher spread0.282 · 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 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

Citations28
Published2014
Admission routes2
Has abstractyes

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