Making the Case for Succession Planning: Who's on Deck in Your Organization?
Bibliographic record
Abstract
In Canada, the nursing shortage is all encompassing, and nurse leaders are needed from the bedside to the boardroom. Healthcare organizations and the nursing profession lag behind the corporate sector in development of strategic leadership succession planning. Contemporary nurse leaders will require all the knowledge, skills, attitudes and competencies their predecessors can provide. Effective leadership development and succession planning will provide a climate that is conducive to the transfer of that knowledge. Providing leadership development opportunities within the context of succession planning will assist nurses to develop and nurture the leader within. A definitive strategic succession plan may mean the difference between success and failure for nurses and their organizations.
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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 | 0.019 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.009 |
| Scholarly communication | 0.014 | 0.014 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.009 | 0.021 |
| 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".