MétaCan
Menu
Back to cohort
Record W2544651592 · doi:10.1097/nna.0000000000000407

The Effect of Authentic Leadership, Person-Job Fit, and Civility Norms on New Graduate Nurses’ Experiences of Coworker Incivility and Burnout

2016· article· en· W2544651592 on OpenAlex
Heather K. Spence Laschinger, Emily Read

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJONA The Journal of Nursing Administration · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicWorkplace Violence and Bullying
Canadian institutionsLondon Health Sciences Centre
Fundersnot available
KeywordsCivilityIncivilityBurnoutJob satisfactionPsychologySocial psychologyClinical psychologyPolitical sciencePolitics

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.359
Threshold uncertainty score0.449

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.091
GPT teacher head0.359
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it