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Record W2020211015 · doi:10.1177/000841740307000506

Supported Employment: Evidence for a Best Practice Model in Psychosocial Rehabilitation

2003· review· en· W2020211015 on OpenAlexaffvenue
Sandra Moll, James Huff, Lisa M. Detwiler

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2003
Typereview
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsSupported employmentPsychosocialVocational rehabilitationVocational educationMental healthBest practicePsychologyRehabilitationOccupational therapyMental illnessEvidence-based practiceOrder (exchange)Applied psychologyNursingMedical educationMedicineBusinessPsychotherapistPsychiatryWork (physics)PedagogyAlternative medicinePolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Traditional approaches to vocational rehabilitation in mental health settings have had only limited effectiveness in enabling clients to meet their employment goals. Within the last decade the individual Placement and Support Model (IPS) has emerged as an alternate, evidence-based approach to providing vocational services with individuals who have severe and persistent mental illness. METHOD AND SCOPE: This review of the literature critically examines research regarding the IPS model of supported employment then discusses implications of this research for occupational therapists. PRACTICE IMPLICATIONS: In order to enable clients to achieve their competitive employment goals, it is imperative that occupational therapists incorporate best practice models of supported employment. IPS is one model that appears to hold significant promise for occupational therapists and their clients.

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)0.025
metaresearch head score (Gemma)0.050
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.025
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.050
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.006
Science and technology studies0.0010.003
Scholarly communication0.0050.005
Open science0.0040.003
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0060.002

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 head0.660
GPT teacher head0.644
Teacher spread0.016 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations42
Published2003
Admission routes2
Has abstractyes

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