The Role of Incentives in Nurses’ Aspirations to Management Roles
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to describe findings from a study examining nurses' perceptions of incentives for pursuing management roles. BACKGROUND: Upcoming retirements of nurse managers and a reported lack of interest in manager roles signal concerns about a leadership shortage. However, there is limited research on nurses' career aspirations and specifically the effect of perceived incentives for pursuing manager roles. METHODS: Data from a national, cross-sectional survey of Canadian nurses were analyzed (n = 1241) using multiple regression to measure the effect of incentives on nurses' career aspirations. RESULTS: Twenty-four percent of nurses expressed interest in pursuing management roles. Age, education, and incentives explained 43% of the variance in career aspirations. Intrinsically oriented incentives such as new challenges, autonomy, and the opportunity to influence others were the strongest predictors of aspirations to management roles. CONCLUSIONS: Ensuring an adequate supply of nurse managers will require proactive investment in the identification, recruitment, and development of nurses with leadership potential.
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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 | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".