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Record W3154246652 · doi:10.1108/pr-04-2019-0172

Servant leadership and mistreatment at the workplace: mediation of trust and moderation of ethical climate

2021· article· en· W3154246652 on OpenAlexaff
Inam Ul Haq, Usman Raja, Imtiaz Alam, Dirk De Clercq, Sharjeel Saleem

Bibliographic record

VenuePersonnel Review · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicWorkplace Violence and Bullying
Canadian institutionsBrock University
Fundersnot available
KeywordsModerated mediationServant leadershipEthical leadershipSocial psychologyPsychologyMediationModerationIncivilityValue (mathematics)OriginalityOstracismPublic relationsLeadership stylePolitical science

Abstract

fetched live from OpenAlex

Purpose With a foundation in social exchange theory, this study examines the relationship between servant leadership and three types of workplace mistreatment – bullying, incivility and ostracism – while also considering a mediating role of trust in the leader and a moderating role of the ethical climate. Design/methodology/approach Three time-lagged sets of data (N = 431) were collected among employees working in various sectors. Findings Servant leadership relates significantly to trust in the leader, as well as to workplace bullying, incivility and ostracism. In turn, trust in the leader mediates the relationship between servant leadership and all three types of workplace mistreatment. The results also indicate the presence of moderated mediation, in that the indirect effect of servant leadership on workplace mistreatment is moderated by the ethical climate. Originality/value This study adds to extant research by examining the mediating mechanism of trust in leaders with servant leadership and workplace mistreatment, along with interactive effects of ethical climate.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.064
GPT teacher head0.336
Teacher spread0.272 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations38
Published2021
Admission routes1
Has abstractyes

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