The clinical nurse educator as a congruent leader: A mixed method study
Bibliographic record
Abstract
Educational leadership in the clinical setting has an influence on the promotion and achievement of competent and confident nurses. In Australia, the newly qualified registered nurse entering the workforce is exposed to a variety of experiential learning opportunities and engages with the nurse who is responsible for the clinical learning and development (clinical nurse educator) in the first-year graduate program. There is limited research examining the clinical nurse educator role and actual and potential leadership in the workforce. This study aimed to articulate the extent to which the clinical nurse educator is perceived as a clinical leader in the acute hospital setting. And specifically, the relationship of the role to the congruent leadership style. A mixed method convergent design (QUANT + QUAL) approach used (1) an online questionnaire with open and closed ended questions for the graduate nurses and (2) semi-structured individual interviews with graduate nurses, their clinical nurse educators and their nurse managers. Findings confirmed the clinical nurse educator leadership was visible, approachable, and relational with clearly identified values and passionate patient-centred principles. Challenges to the clinical nurse educator identity and confidence exist and impact the clinical role and leadership value. The clinical nurse educator did not need to be in a management position to lead and influence graduates’ successful transition to practice and integration into the clinical environment. The clinical nurse educator exhibits a congruent leadership style through engagement and promotion of the graduate nurses in their first year of nursing. The education role is of significance to meet contemporary health care expectations and promote quality patient care and new nurse retention in the healthcare organisation.
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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 | 0.025 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".