Incentivizing Full-time Employment for New Graduate Nurses in Ontario: Impact of Policy on Care
Bibliographic record
Abstract
There is consensus that a professional full-time nursing workforce leads to better patient outcomes and a safer health care environment. In 2007, the Ontario Ministry of Health and Long-Term Care introduced the Nursing Graduate Guarantee (NGG), a policy mechanism designed to strengthen the nursing workforce by increasing full-time (FT) employment for newly graduated nurses. Several factors have affected the supply and employment status of nurses in the province over the past two decades, including the introduction of unregulated health care workers and crises such as SARS and COVID-19. A secondary analysis of the College of Nurses of Ontario registration database was conducted to identify and evaluate trends in the supply and employment of nurses in Ontario prior to and following introduction of the NGG. The results demonstrate that full-time employment of new registered nurses and new registered practical nurses initially increased but has since fallen to below pre-policy levels. Part-time work among newly graduated nurses is increasing across all sectors, signaling a diminishing effect of the NGG investments over time. Investments in health human resources have a stabilizing effect on the nursing workforce. Ensuring an adequate number of nurses is necessary for crisis preparation, management and recovery, particularly in sectors with low surge capacity such as long-term care. However, sustained financial, political, public, and professional support is required.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".