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Record W2991608307 · doi:10.1017/jmo.2019.76

The relationship between workplace incivility and depersonalization towards co-workers: Roles of job-related anxiety, gender, and education

2019· article· en· W2991608307 on OpenAlexaff
Dirk De Clercq, Inam Ul Haq, Muhammad Umer Azeem

Bibliographic record

VenueJournal of Management & Organization · 2019
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsBrock University
Fundersnot available
KeywordsDepersonalizationPsychologySocial psychologyAnxietyScholarshipFeelingEmotional exhaustionClinical psychologyPolitical scienceBurnout

Abstract

fetched live from OpenAlex

Abstract This study contributes to management scholarship by unpacking the relationship between employees' exposure to workplace incivility and their exhibition of depersonalization towards co-workers, according to the mediating effect of job-related anxiety and the moderating effects of gender and education. Time-lagged data from employees in Pakistani organizations show that an important reason workplace incivility enhances depersonalization towards co-workers is that employees feel anxious about their jobs. This mediating role of job-related anxiety is particularly salient among male and higher-educated employees, possibly because they suffer from resource losses in the form of dignity threats when they are treated with disrespect. For organizations, this study accordingly pinpoints a key mechanism by which disrespectful workplace treatment can escalate into depersonalization towards co-workers (enhanced job-related feelings of anxiety), as well as how the strength of this mechanism might depend on individual factors.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0040.000

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 head0.036
GPT teacher head0.357
Teacher spread0.321 · 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

Citations58
Published2019
Admission routes1
Has abstractyes

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