Going Through the Motions: Policy Considerations for Addressing Mental Health-Related Worker Presenteeism in Canada
Bibliographic record
Abstract
As mental illnesses in Canada have become more prevalent, a deeper examination of some key issues is required. One significant concern related to mental health is that it gives way to presenteeism – the phenomenon of employees being physically present at work but performing below capacity due to illness. This leaves workers experiencing worsened mental health outcomes and costs employers billions of dollars in lost productivity. The policy environment post COVID-19 has focused attention on mental illness as a disability and reviewing access to relevant programs that can be accessed to alleviate the financial concerns and health insecurities of people with mental illnesses. This project uses the United Nations Convention of the Rights of Persons with Disabilities (CRPD) as a guiding framework to explore alignment between rights based commitments and the current landscape of workplace disability benefit programs in Canada geared towards providing income support for people needing to take time away from work due to mental illnesses. It evaluates those programs and in doing so, isolates some potentially beneficial policy considerations that could be used in the reform of existing programs or the implementation of new ones that could address mental health-related presenteeism in Canada.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.005 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.019 | 0.001 |
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".