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Record W2587052875 · doi:10.1002/job.2183

Targeted workplace incivility: The roles of belongingness, embarrassment, and power

2017· article· en· W2587052875 on OpenAlexaff
M. Sandy Hershcovis, Babatunde Ogunfowora, Tara C. Reich, Amy M. Christie

Bibliographic record

VenueJournal of Organizational Behavior · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicWorkplace Violence and Bullying
Canadian institutionsWilfrid Laurier UniversityUniversity of Calgary
Fundersnot available
KeywordsEmbarrassmentIncivilityBelongingnessPsychologyFeelingSocial psychologyPower (physics)Job insecurityWork (physics)

Abstract

fetched live from OpenAlex

Summary Research to date has largely been unclear about whether a single perpetrator is sufficient to instigate the well‐documented negative consequences of workplace incivility. In the current research, we examine the extent to which perceived belongingness and embarrassment mediate the relationship between incivility from a single perpetrator and two important outcomes (job insecurity and somatic symptoms), and the extent to which the perpetrator's power moderates these relationships. Across two studies using different methods, we find that incidents of single perpetrator incivility are associated with target feelings of isolation and embarrassment, which in turn relate to targets' perceived job insecurity and somatic symptoms (Studies 1 and 2) both the same day and three days later (Study 2). Moreover, we find that perpetrator power moderates the relationship between incivility and embarrassment, such that targets are more embarrassed when the perpetrator is powerful. Implications for theory and practice are discussed. Copyright © 2017 John Wiley & Sons, Ltd.

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)0.017
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 score0.004
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0010.003
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 head0.014
GPT teacher head0.303
Teacher spread0.289 · 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

Citations122
Published2017
Admission routes1
Has abstractyes

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