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Record W2166236632 · doi:10.1177/0018726710364163

The role of justice and social exchange relationships in workplace deviance: Test of a mediated model

2010· article· en· W2166236632 on OpenAlexaff
Assâad El Akremi, Christian Vandenberghe, Julie Camerman

Bibliographic record

VenueHuman Relations · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsDeviance (statistics)Procedural justicePsychologySocial psychologyInterpersonal communicationSocial exchange theoryOrganizational justiceDistributive justiceInteractional justiceInterpersonal relationshipOrganizational commitmentEconomic JusticePolitical science

Abstract

fetched live from OpenAlex

Using data collected on two occasions spaced apart by three months ( N = 602), we examined the relationships between a) distributive, procedural, informational, and interpersonal justice (measured at Time 1) and b) perceived organizational support (POS), leader—member exchange (LMX), and organization- and supervisor-directed deviance (measured at Time 2). We found that POS fully mediated the relationship of procedural justice but not distributive justice to organization-directed deviance. In addition, LMX fully mediated the relationships of informational justice and interpersonal justice to both supervisor-directed deviance and organization-directed deviance. The implications of these findings for the study of justice and social exchange relationships as predictors of workplace deviance 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.

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)0.011
metaresearch head score (Gemma)0.041
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 score0.011
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.041
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.027
GPT teacher head0.253
Teacher spread0.227 · 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

Citations139
Published2010
Admission routes1
Has abstractyes

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