Clinical nurse leaders in the community: Building an academic faculty practice partnership
Bibliographic record
Abstract
The Affordable Care Act (ACA) emphasis on preventive care and primary health has given community organizations and outpatient care environments renewed attention. Nursing has been offered the opportunity to lead healthcare into a new era. One of the two new nursing programs to be given life in this movement is the Clinical Nurse Leader (CNL). The CNL is a graduate level educated nurse who specializes in healthcare systems leadership, a facilitator of care in the complex healthcare environments of today. They are equipped to see the wider and broader perspective of things, assess needs, research the best interventions for problems identified, implement these interventions, and evaluate the processes and outcomes of the interventions. This paper describes the experience of a school of nursing and health professions and a community non-profit organization in developing a community faculty practice partnership allowing for CNL, nurse practitioner, and Doctorate of Psychology students to be placed at a community clinic serving high-risk patients. The Synergy Model of community partnership formation by Lasker and Weiss is used as the complimentary model to show how the CNL approach to a microsystem can be effectively adopted into the community setting with beneficial outcomes to both parties of the partnership.
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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 | 0.033 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.027 | 0.012 |
| Scholarly communication | 0.017 | 0.012 |
| Open science | 0.005 | 0.034 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".