Running on Empty: Ontario Hospital Workers’ Mental Health and Well-Being Deteriorating Under Austerity-Driven System
Bibliographic record
Abstract
The well-being of health care workers (HCWs) and the public in Ontario, Canada is at risk as the province's health care system is strained by neoliberal restructuring and an aging population. Deteriorating working conditions that preceded the COVID-19 pandemic further declined as the added challenges took their toll on the work force, physically and mentally. The pandemic-weary hospital staff, predominantly women, many racialized, are facing unprecedented challenges. They are experiencing stress, anxiety, and burnout from staffing shortages and the resulting increased workloads, long hours, and violence. Comprehensive telephone interviews were conducted with 26 HCWs from less highly paid occupations in a range of hospitals across the province. Thematic analysis reveals a critical need for policies and legislation ensuring increased funding, hospital capacity, and reduced wait times while providing HCWs with fair and equitable wages, increased staffing, mental health supports, greater respect and acknowledgment, and strong protections from violence and other workplace hazards.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.030 | 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".