Administration: Nursing Entrepreneurship: Instilling Business Acumen into Nursing Healthcare Leadership
Bibliographic record
Abstract
Nursing leaders have traditionally held leading roles in healthcare. For years, nurses have articulated and advocated collaborative and shared visions of care delivery. We have co-created models of care that have emphasized caring and responsiveness to individual and family (customer) needs. We have acted as strategic and operational connectors, individuals who sat at organizational senior tables informing administrative strategic and operational decisions with an understanding of the impact a particular decision might have on an individual’s care. Nursing leaders have served as a valued “check and balance,” competent professionals schooled in the complex systems of healthcare who could ensure that decisions made by an organization’s administrative leadership were at least informed by the reality of the clinical situation. In short, we have been valued organizational leaders. Recently, however, nurses appear to have become less important as strategic team players. Over the past decade, nursing has experienced much restructuring, downsizing and rightsizing. The result has been a loss of nursing leadership infrastructure. Many nursing leaders have lost the word “nursing” in their titles. Some nurse executives no longer report to the CEO; some do not even sit at the senior table. We have seen a marginalization of our strategic impact, and we have suffered a loss of morale within the profession. Arguably, healthcare planning and delivery have also suffered. Why has nursing lost this traditional leadership role? I would suggest that we must start by recognizing the reality of today’s healthcare agenda and how our profession is Nursing Entrepreneurship: Instilling Business Acumen into Nursing Healthcare Leadership
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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 | 0.008 | 0.009 |
| 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 | 0.010 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 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".