Bibliographic record
Abstract
As today's workplaces strive toward a climate of inclusiveness for persons with disabilities, much work remains for employers in developing a process to achieve this ideal. While survivors of mental illness are encouraged to disclose related concerns to their employer, such sharing of personal information remains daunting. Similarly, employers attempting to assist the process are often awed by the extent of collaborations involved in integrating employees with mental health issues back to work as well as concern about compliance with human rights legislation. Needed accommodations in terms of approach to the work itself are often simple; however substantiating the need for adjustments is more complex. This case study introduces a model to support the development of shared goals and shared understandings for return to work (RTW) among workers with mental health concerns, employers, co-workers and therapists. The model of occupational competence is used as a basis to guide dialogue, identify challenges and generate solutions that take into consideration a worker's preferences, sensitivities, culture and capacities in relationship to the occupational demands in a given workplace environment. A case study is used to demonstrate the potential utility of the model in assisting stakeholders to strengthen collaborations and partnering to achieve a shared understanding of worker and workplace needs.
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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 | 0.006 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.021 | 0.004 |
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".