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Record W2791259755 · doi:10.1177/0143831x17744029

The relationship between psychological contract breach and counterproductive work behavior in social enterprises: Do paid employees and volunteers differ?

2018· article· en· W2791259755 on OpenAlexaff
Yannick Griep, Tim Vantilborgh, Samantha K. Jones

Bibliographic record

VenueEconomic and Industrial Democracy · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsFeelingPsychological contractCounterproductive work behaviorPsychologySocial psychologyMediationPsychological interventionModerated mediationBootstrapping (finance)Work (physics)Organizational commitmentOrganizational citizenship behaviorBusinessSociologyFinance

Abstract

fetched live from OpenAlex

Scholars agree that counterproductive work behavior (CWB) is instigated by psychological contract breach and feelings of violation. This article focuses on the mediating role of feelings of violation (a mixture of negative emotions) in the relationship between psychological contract breach and CWB, and assesses whether volunteers and paid employees experience a similar chain of events. The study uses Mplus 7 to estimate a moderated mediation model with bootstrapping. The results indicate that both paid employees and volunteers (1) experience feelings of violation when perceiving psychological contract breach, and (2) engage in CWB targeted to the organization (CWB-O) when experiencing feelings of violation. However, these relationships were not significantly different when comparing paid employees and volunteers. It is hence concluded that a similar chain of cognitions and emotions explains why volunteers and paid employees engage in CWB-O. In unraveling this sequence, possibilities for targeted interventions are suggested.

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 score0.008
Threshold uncertainty score0.517

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.049
GPT teacher head0.290
Teacher spread0.240 · 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

Citations54
Published2018
Admission routes1
Has abstractyes

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