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Record W2066188371 · doi:10.1037/a0020723

How rude! Emotional labor as a mediator between customer incivility and employee outcomes.

2010· article· en· W2066188371 on OpenAlex

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.

Bibliographic record

VenueJournal of Occupational Health Psychology · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicEmotional Labor in Professions
Canadian institutionsNovelis (Canada)
Fundersnot available
KeywordsIncivilityEmotional laborEmotional exhaustionPsychologyBurnoutService qualitySocial psychologyStressorOccupational stressApplied psychologyService (business)BusinessMarketingClinical psychology

Abstract

fetched live from OpenAlex

Because of the large number of people employed in service occupations, customer incivility has become an increasingly prevalent and important workplace stressor. Unfortunately, relatively little research has examined the effects of customer incivility; of the research that does exist, virtually all of it has focused solely on employee mental health outcomes. The present study was designed to replicate previous research linking customer incivility to the emotional exhaustion dimension of burnout and to expand on previous research by examining the effects of customer incivility on customer service quality. In addition, two models were proposed and tested in which emotional labor mediated the relationship between customer incivility and outcomes. Data from 120 bank tellers revealed that customer incivility was positively related to emotional exhaustion and negatively related to customer service performance. In addition, both proposed models were supported. Theoretical and practical implications of the findings and future directions are discussed.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.157
Threshold uncertainty score0.608

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.082
GPT teacher head0.505
Teacher spread0.422 · 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