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Record W2152667480 · doi:10.7202/014813ar

Le maintien en emploi de personnes souffrant d’une maladie mentale

2007· article· fr· W2152667480 on OpenAlexafffundvenue
Marc Corbière, Alain Lesage, Kathe Villeneuve, Céline Mercier

Bibliographic record

VenueSanté mentale au Québec · 2007
Typearticle
Languagefr
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsInstitut universitaire en santé mentale de MontréalUniversité de MontréalUniversité de Sherbrooke
FundersMinistère de la Santé et des Services sociaux
KeywordsMental illnessPsychologyWork (physics)Mental healthJob placementPsychiatry

Abstract

fetched live from OpenAlex

Work integration for people with mental illness is complex and difficult. For those who obtain employment, job tenure is typically brief. The purpose of this article is to identify the personal determinants of job tenure of people with severe mental illness registered in prevocational programs. Out of 105 people with mental illness who are employed during the nine month follow-up after their registration in a prevocational program, close to 50 % kept their first job. According to the job tenure indicators (first or last job obtained), the results from survival analyses show that the significant variables are related to background characteristics (financial aid), work-related characteristics (length of absence from the workplace, type of job), cognitive (executive functions), and clinical aspects (paranoid symptoms). In conclusion, the authors propose not only to assess personal variables to better understand the work integration process for people with mental illness, but also to conduct a systematic evaluation of the job site.

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)0.002
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 score0.867
Threshold uncertainty score0.265

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.013
GPT teacher head0.289
Teacher spread0.277 · 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

Citations21
Published2007
Admission routes3
Has abstractyes

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