Should health care institutions provide job accommodations for health care workers with serious mental health concerns during the COVID-19 pandemic?
Bibliographic record
Abstract
As the Coronavirus Disease 2019 pandemic continues, increased attention has been given to its mental health impacts on frontline health care workers. There is a consensus, consistent with established standards applicable to the duty to treat, that health care workers who are especially vulnerable to risk of physical harm should be provided job accommodations to reduce their risk of disease exposure, but it is unclear whether health care workers should be provided similar accommodations if their vulnerability relates specifically to mental health concerns. Especially given emerging evidence that the pandemic is taking a heavy toll on the mental health of health care workers, this issue should be included in policy conversations involving support of health care workers and provision of resources to them during the pandemic. Arguments in favor of expanding accommodations to those with mental health concerns include institutions’ ethical duty to protect vulnerable workers and not discriminate against their employees, as well as broader consideration of the consequences of not providing accommodations, both for health care workers and patients.
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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 | 0.017 | 0.081 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.015 | 0.009 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".