A time-lagged analysis of the effect of authentic leadership on workplace bullying, burnout, and occupational turnover intentions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Destructive interpersonal experiences at work result in negative feelings among employees and negative work outcomes. Understanding the mechanisms through which bullying can lead to burnout and subsequent turnover is important for preventing and managing this problem. Leaders play a key role in shaping positive work environments by discouraging negative interpersonal experiences and behaviours. The aim of this study is twofold. Specifically we aim to examine the relationship between authentic leadership and new graduate nurses experiences of workplace bullying and burnout over a 1-year timeframe in Canadian healthcare settings. Furthermore we aim to examine the process from workplace bullying to subsequent burnout dimensions, and to job and career turnover intentions. Results of structural equation models on new graduate nurses working in acute care settings in Ontario (N = 205) provide support for the hypothesized model linking supervisor's authentic leadership, subsequent work-related bullying, and burnout, and these in turn to job and career turnover intentions. Thus, the more leaders were perceived to be authentic the less likely nurses’ were to experience subsequent work-related bullying and burnout and to want to leave their job and profession. The results highlight the important role of leadership in preventing negative employee and organizational outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it