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Record W4293052087 · doi:10.1080/00208825.2022.2115369

Mitigating the risk that peer-initiated task conflict escalates into diminished helping: roles of passion for work and collectivistic orientation

2022· article· en· W4293052087 on OpenAlexaff
Dirk De Clercq, Renato Pereira

Bibliographic record

VenueInternational Studies of Management and Organization · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsBrock University
Fundersnot available
KeywordsPassionPsychologyCollectivismSocial psychologyTask (project management)Interpersonal communicationWork (physics)CONTESTApplied psychologyPolitical scienceIndividualismManagement

Abstract

fetched live from OpenAlex

This study unravels the link between employees’ exposure to peer-initiated task conflict—defined as the extent to which they perceive that coworkers systematically contest and attack their opinions—and their engagement in helping behavior. Beliefs about interpersonal conflict might mediate this link, and two personal resources, passion for work and collectivistic orientation, arguably have moderating roles. To test these predictions, this study relies on survey data from employees who work in the banking sector, which confirm that peer-initiated task conflict diminishes helping behavior, because the focal employees come to believe coworkers are responsible for their emotion-based quarrels. Employees’ passion for work and collectivistic orientation buffer this harmful dynamic. Organizations thus should recognize that exposure to overcritical colleagues can undermine voluntary work behaviors, as well as consider how they might help reduce the force of this negative dynamic by enabling employees to find ways to draw from their supportive personal resources.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.021
Threshold uncertainty score0.500

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.025
GPT teacher head0.267
Teacher spread0.242 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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