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Record W4398774294 · doi:10.1108/joepp-11-2023-0528

How coworker undermining leads justice-sensitive employees to miss deadlines

2024· article· en· W4398774294 on OpenAlexaff
Dirk De Clercq, Muhammad Umer Azeem, Inam Ul Haq

Bibliographic record

VenueJournal of Organizational Effectiveness People and Performance · 2024
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsBrock University
Fundersnot available
KeywordsEconomic JusticeBusinessOrganizational justiceSocial psychologyPsychologyLaw and economicsPublic relationsPolitical scienceSociologyLawOrganizational commitment

Abstract

fetched live from OpenAlex

Purpose This study examines how employees’ exposure to coworker undermining may lead them to miss work deadlines. It offers a particular focus on the mediating role of diminished organization-based self-esteem and the moderating role of justice sensitivity in this connection. Design/methodology/approach The research hypotheses are tested with data collected among employees and supervisors who work in various industries. Findings Purposeful efforts by coworkers to cause harm translate into an increased propensity to fail to complete work on time, because the focal employees consider themselves unworthy organizational members. The extent to which employees feel upset with unfair treatments invigorates this process. Practical implications For employees who are frustrated with coworkers who deliberately compromise their professional functioning, diminished self-worth in relation to work and the subsequent reduced willingness to exhibit timely work efforts might make it more difficult to convince organizational leaders to do something about the negative coworker treatment. Pertinent personal characteristics can serve as a catalyst of this dynamic. Originality/value This study contributes to extant human resource management research by detailing the link between coworker undermining and a reduced propensity to finish work on time, pinpointing the roles of two hitherto overlooked factors (organization-based self-esteem and justice sensitivity) in this link.

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 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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.526

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.042
GPT teacher head0.406
Teacher spread0.364 · 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 teacher head, 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

Citations0
Published2024
Admission routes1
Has abstractyes

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