Future ready: Strengthening oncology nursing leadership in the context of professional oncology nursing organizations.
Bibliographic record
Abstract
Every nurse is a leader. Rather than being situated only within a traditional leadership role or title, nursing leadership is about critical thinking, action and advocacy across all roles, practice settings and domains of nursing practice. When high-quality nursing leadership is enacted, positive patient, provider and system outcomes are demonstrated (Cummings et al., 2010; National Expert Commission, 2012; Wong, Cummings & Ducharme, 2013). Leadership begins in undergraduate education and continues throughout one’s career. Nursing leadership in this context is about looking beyond nursing, as a series of scientific acts of caring that can change individual lives, to include lifelong commitment to political action for system change. It requires nurses to lift their gaze from focusing only on individuals to populations, and from the local to global context (Canadian Nurses Association, 2009; Institute of Medicine, 2011; International Council of Nurses, 2016; National Expert Commission, 2012).
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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 | 0.011 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.020 | 0.022 |
| Insufficient payload (model declined to judge) | 0.014 | 0.013 |
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".