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Record W2407659625

[Homelessness, mental health and occupational therapy.].

2000· article· en· W2407659625 on OpenAlexaboutno aff
Joyce Tryssenaar, Suzanne Wilkinson, C R Bailey

Bibliographic record

VenuePubMed · 2000
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
Fundersnot available
KeywordsOccupational therapyMental healthPopulationMental illnessPsychologyMedicinePsychiatryEnvironmental health
DOInot available

Abstract

fetched live from OpenAlex

Persons who are homeless with a mental illness constitute a significant portion of the homeless population. They have a myriad of occupational performance problems and are further compromised by systemic and political issues. There is growing evidence that occupational therapy can make a contribution to the health and quality of life of this marginalized, under served population. This paper describes the process and challenges providing occupational therapy services to persons who are homeless with mental health problems, addictions, and serious mental illnesses using the Canadian Model of Occupational Performance. There is a goodness of fit between the values and beliefs of the occupational therapy profession and the needs and occupational performance issues of persons who are homeless. Through helping people to develop meaningful occupations and gain control of their lives, people may be able to make permanent and positive changes in their lives. Within this dynamic is a great deal of potential learning and growth for human beings regardless if they are providers or recipients of service.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.039
Threshold uncertainty score0.130

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0020.003
Open science0.0010.003
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0390.009

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 head0.164
GPT teacher head0.458
Teacher spread0.294 · 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

Citations1
Published2000
Admission routes1
Has abstractyes

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