The Imperative for New Approaches for Managing and Leading in Healthcare for the 21st Century
Bibliographic record
Abstract
The Canadian healthcare system must change to meet current and future realities, particularly to respond effectively to changing age and cultural demographics and new medical/scientific technologies. To meet its ongoing policy role, the Canadian Nurses Association established a National Expert Commission in 2011, mandated to prepare a report on healthcare reform and transformation, with a clear focus on the role individual nurses and the nursing profession generally could play in ensuring better health, better care and better value for Canadians. In this paper, Commission co-chair, health law specialist Maureen McTeer, outlines the key findings and recommendations of their final report, titled A Nursing Call to Action: The Health of our Nation, the Future of our Health System which she and co-chair Dr. Marlene Smadu presented originally at the CNA's biennial meeting in Vancouver, in June, 2012. The discussion focuses on the rationale behind the commission's recommendation for a new registered nursing education curriculum and approach to training.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.023 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.026 | 0.042 |
| Scholarly communication | 0.032 | 0.017 |
| Open science | 0.005 | 0.018 |
| Research integrity | 0.010 | 0.022 |
| Insufficient payload (model declined to judge) | 0.017 | 0.005 |
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".