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Record W2607107441 · doi:10.5539/ass.v13n5p165

The Mediating Effect of Affective Organizational Commitment in the Relationship between Organizational Justice and Organizational Citizenship Behavior: A Conceptual Model

2017· article· en· W2607107441 on OpenAlexvenueno aff
Mohammad Zayed, Junaimah Jauhar, Zurina Mohaidin

Bibliographic record

VenueAsian Social Science · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsOrganizational citizenship behaviorOrganizational justiceOrganizational commitmentPsychologySocial psychologySocial exchange theoryContext (archaeology)Affective events theoryOrganizational behavior and human resourcesOrganizational learningMeaning (existential)Interactional justiceConceptual modelJob performanceKnowledge managementJob satisfactionEpistemology

Abstract

fetched live from OpenAlex

A literature review revealed that the effect of organizational justice on organizational citizenship behavior (OCB) had been heavily examined as an overall relationship. However, there is a lack of research that examined the effect of organizational justice dimensions on OCB via affective organizational commitment as a mediator. Therefore, this research is an attempt to provide a value theoretical model that explains the relationships between dimensions of organizational justice and OCB as well as tries to describe in detail meaning of this relationship through the mediating effect of affective organizational commitment in the context of social exchange theory. Furthermore, the proposed hypotheses on the link between these variables are provided as a foundation for further research.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.032
GPT teacher head0.298
Teacher spread0.266 · 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 designTheoretical or conceptual
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

Citations17
Published2017
Admission routes1
Has abstractyes

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