Work Values of People With Severe Mental Disorders Registered in Vocational Programs: Validation of the Work Values Questionnaire
Bibliographic record
Abstract
Though several instruments have been developed for measuring work values in the general population, at present no instrument has been validated for people with mental disorders seeking a job. Employment specialists could use such a questionnaire to help people with severe mental disorders to get competitive employment, and consequently to maintain employment, as a pitfall for this population is job tenure. The Questionnaire de Valeurs de Travail (QVT), translated into English as the Work Values Questionnaire (WVQ), measures five work values: climate, status, risk, realization, and freedom. Our study's objectives were (a) to validate the QVT in individuals with mental disorders seeking a job; (b) to create a short version of the QVT; (c) to classify people on the basis of their work-value patterns, and (d) to compare these profiles on the basis of work outcomes and related personal characteristics. Individuals with severe mental disorders (N = 254) registered in vocational programs filled in the QVT. The confirmatory factor analysis showed reasonable fit indices for the 58-item QVT and good fit indices for the 30-item QVT shortened form. People who placed a higher importance on work values were employed more often in competitive employment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".