Bibliographic record
Abstract
This research used an interpretivist exploratory case study design to examine how thirty nursing deans, directors or chairs (nursing deans) from 28 English language Canadian universities led institutional operations, set future direction and facilitated organizational decision-making. Leadership in universities has been described as a hybrid mix of traditional and entrepreneurial approaches (Collinson & Collinson, 2009). The administrator as conservator (Terry, 2003) and entrepreneurial public servant (Rowley, Lujan & Dolence, 1997) leadership models, which together form a leadership continuum, served as the foundation for describing, analyzing and interpreting this study' s findings. The nursing deans were found to use forty-nine leadership practices, thirty-seven (76%) of which reflected entrepreneurial public servant leadership. This signifies that these nursing deans used a blended leadership approach with entrepreneurial public servant practices being dominant. Personal values, globalization, university systems, structures and priorities, internal relationships, academic networks and mentors influenced the nursing deans ' entrepreneurial public servant leadership practices. The researcher also examined the amount of time that these nursing deans spent completing tasks in eight role function areas associated with the deanship position (Salewski, 2002). Approximately seventeen hours (30%) and eight hours (14%) of their 62 hour work week were spent completing tasks in the human resources/personnel and professional leadership/research role function areas respectively. This first national study of the Canadian university nursing deanship substantiated the shortage of nursing deans in Canada. At the time they were interviewed, 30 per cent of the nursing deans were holding acting or interim appointments. The turnover of nursing deans approximated 30 per cent between 2007 and 2009 and increased to 60 per cent by 2011. Senior university leaders can use the findings of this study as one foundation for reshaping the nursing deanship so that it becomes a more viable career option. The research also fulfills long-standing scholarly recommendations to study how university deans lead faculties (de Boer & Goedegebuure, 2009 ; Boyett, 1996) and offers a glimpse into the Canadian university deanship, which is understudied (Boyco & Jones, 2010).
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.017 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 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".