The Effect of Authentic Leadership, Person-Job Fit, and Civility Norms on New Graduate Nurses’ Experiences of Coworker Incivility and Burnout
Bibliographic record
Abstract
OBJECTIVE: This study examined the influence of authentic leadership, person-job fit with 6 areas of worklife, and civility norms on coworker incivility and burnout among new graduate nurses. BACKGROUND: New graduate nurses report experiencing high levels of workplace incivility from coworkers, which has been found to negatively impact their job and career satisfaction and increase their intention to leave. The role of civility norms in preventing burnout and subsequent exposure to incivility from coworkers has yet to be examined among new graduate nurses. METHODS: A cross-sectional mail survey of 993 new graduate nurses across Canada was conducted. RESULTS: The results supported the hypothesized relationships between study variables. CONCLUSIONS: Civility norms play a key role in preventing early career burnout and coworker incivility experienced by new graduate nurses. Leaders can influence civility norms by engaging in authentic leadership behaviors and optimizing person-job fit.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".