A Case Study of Students' Experiences and Nursing Educators' Leadership Practices to Facilitate RPN to BScN Professional Socialization
Bibliographic record
Abstract
This interpretive qualitative case study of nursing educators’ facilitation of bridging students’ professional socialization in support of their transition from RPN to BScN in the context of one Canadian Registered Practical Nurse (RPN) to Baccalaureate of Science in Nursing (BScN) bridging program explored: (1) how nursing educators understand bridging students’ professional socialization; (2) what leadership practices they use to facilitate professional socialization; (3) how bridging students understand these leadership practices in support of their professional socialization; and, (4) what programmatic support nursing clinical educators receive to support bridging students. Transition, professional socialization, and leadership practice constitute this study’s conceptual framework. Kouzes and Posner’s exemplary leadership practices framework was used to interpret nursing educators’ leadership practices. Data were collected from interviews with nursing clinical educators and program coordinators, from focus groups with bridging students and graduates, and from one program document. Bridging students experience a unique professional socialization trajectory, not only impacted by interactions with nursing educators but by broader intra-professional, organizational, regulatory, and bridging program structural factors. Nursing educators across educational areas facilitate professional socialization using teaching and leadership practices in tandem; the use of a leadership theory with an instructional component is suggested. Nursing educators should consider the professional socialization trajectory in curriculum planning and to guide their leadership and teaching practices, and extend their influence on professional socialization outside the spaces where they typically interact with students. Nursing clinical educators are under-supported in their work with bridging students; improved programmatic support is needed.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.006 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".