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Record W1976316528 · doi:10.1176/ps.2006.57.4.558

Open Forum: Surviving the Tornado of Mental Illness: Psychiatric Survivors' Experiences of Getting, Losing, and Keeping Housing

2006· article· en· W1976316528 on OpenAlexafffundabout
Cheryl Forchuk, Catherine Ward‐Griffin, Rick Csiernik, Katy Turner

Bibliographic record

VenuePsychiatric Services · 2006
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsWestern University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsGriffinPopulationMental illnessPsychiatryPsychologyMental healthSociologyDemographyHistory

Abstract

fetched live from OpenAlex

This qualitative study explored experiences of psychiatric consumer-survivors related to housing. Nine focus groups involving 90 people were conducted in urban and rural areas in South-Western Ontario. A set of open-ended questions was used. Many participants described a devastating experience of losing much of what was important to them and going through a long arduous process to rebuild their lives. Group discussions were audiotaped and transcribed. Individual and team analyses of the transcripts revealed that psychiatric survivors experienced three levels of upheaval, loss, and destruction, similar to the effects of a tornado: losing ground, struggling to survive, and gaining stability. Within each of these levels, five major themes were identified: living in fear, losing control of basic human rights, attempting to hold onto and create relationships, identifying supports and seeking services, and obtaining personal space and place. A caring community response, including adequate housing, income support, and community care, can help people rebuild their lives.

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)0.004
metaresearch head score (Gemma)0.008
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 score0.009
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.009
Scholarly communication0.0020.003
Open science0.0010.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.018
GPT teacher head0.353
Teacher spread0.336 · 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

Citations31
Published2006
Admission routes3
Has abstractyes

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