Utility of the workplace participation domain of the Youth and Young-adult Participation and Environment Measure (Y-PEM): Stakeholder’s perspectives
Bibliographic record
Abstract
BACKGROUND: Assessing workplace participation of people with disability using measures that can inform practice is vital. OBJECTIVE: To investigate the utility of the Youth and young-adult Participation and Environment Measure’s (Y-PEM) Workplace Participation domain. METHOD: Four focus groups were conducted with 11 stakeholders from different employment-related settings. Open-ended questions regarding Y-PEM’s interpretation, meaning and relevance, drawing on elements of clinical utility, were used. Data were analyzed by two investigators using inductive thematic analysis. RESULTS: Stakeholders’ experience in providing/receiving employment services varied (1– 16 years). Three themes emerged. The Y-PEM captures multiple factors in employment transition; it generates insights and sparks conversations to better appreciate and support individuals’ transitioning to employment. Y-PEM meets the need for tools to guide services of transitioning to employment as it is comprehensive in assessing participation and the environment, can provide a “snapshot” of where the young person is at in their transition, and serves different purposes. The tool provides a “piece of the pie” within this complex process and could be used in conjunction with other tools. CONCLUSION: Y-PEM was perceived as essential, comprehensive, and appropriate for use in clinical and employment-related service contexts to inform practice, and guide stakeholders’ decision-making in facilitating transitioning to 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 | 0.050 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 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".