Supply and Demand for Cardiac Nurses in Ontario: Perceptions of CNOs
Bibliographic record
Abstract
This article presents the results of a nursing survey of cardiac care hospitals undertaken by a Cardiac Care Network of Ontario Consensus Panel on Cardiovascular Human Resources. The focus of the Panel was to identify areas of current or pending shortages in human resources and make recommendations to the Ministry of Health and Long-Term Care about human resource management in adult cardiac care in Ontario. The article presents the number and mix of full-time, part-time and casual nursing staff, the age distribution of RNs, and the number of vacant Registered Nurse (RN) positions for a sample of cardiac care hospitals in Ontario. Next a sample of Chief Nursing Officer opinions about factors contributing to current difficulties in recruiting RNs and the outlook for future shortages are presented. Implications for nurse managers are offered, including development of new recruitment and retention strategies, identification of further efficiencies in care provision, and a need for nurse manager involvement in debates about the future of how health care is provided 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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".