The Autonomous-Collaborative Care Model: Meeting the Future Head On
Bibliographic record
Abstract
As care needs continue to increase in complexity in inpatient settings, and nurses' scope of practice evolves to keep pace with these changing demands, it is imperative that nurse leaders ensure nursing care delivery models are well aligned to current realities. Older, traditional models of nursing service may no longer foster safe, effective and efficient care or contribute to job satisfaction and high-quality work life for nurses. This paper describes the Autonomous-Collaborative Care Model and its application in a continuing care setting. This innovative and flexible model fosters autonomy and accountability in nursing practice, reduces duplication in the execution of nursing tasks, enhances effective communication and outlines mechanisms for collaboration among various members of the nursing and interprofessional teams. The model has positioned the authors' organization to meet impending shortages of nursing personnel by ensuring that the right category of nurse is assigned to the appropriate patient, by reducing non-nursing work and by supporting nurses' autonomy to practise to their full scope.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".