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Record W1521480919 · doi:10.1002/hrm.21555

Organizational Citizenship Behavior and Role Breadth: A Meta‐Analytic and Cross‐Cultural Analysis

2013· article· en· W1521480919 on OpenAlexaff
Changquan Jiao, David A. Richards, Rick D. Hackett

Bibliographic record

VenueHuman Resource Management · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsMcMaster UniversityLakehead University
Fundersnot available
KeywordsOrganizational citizenship behaviorCourtesyPsychologyConscientiousnessSocial psychologySupervisorCivic virtueHuman resource managementOrganizational commitmentManagementPersonalityBig Five personality traitsPolitical science

Abstract

fetched live from OpenAlex

Abstract We provide a meta‐analysis of the empirical literature concerning role breadth, defined as the degree to which employees consider organizational citizenship behavior (OCB) to be an inherent part of their job. Results based on a combined sample size of 9,222 showed: (a) Confucian Asians consider OCB as part of their job to a greater extent than do their Anglo counterparts; (b) affiliative kinds of OCB (e.g., helping, conscientiousness, and courtesy) are more likely to be considered part of one's job than are change‐oriented OCB (e.g., voice, taking charge, and initiative); and (c) OCB‐inclusive role breadth correlates strongly with OCB (rc= .43). The implications of these findings for human resources practice, such as competency modeling, employee selection and training, organizational rewards, and employee‐employer/supervisor relations, are discussed. © 2013 Wiley Periodicals, Inc.

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)0.037
metaresearch head score (Gemma)0.079
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.037
Threshold uncertainty score0.195

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0370.079
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.022
Bibliometrics0.0090.010
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.024
GPT teacher head0.258
Teacher spread0.233 · 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 designMeta-analysis
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

Citations52
Published2013
Admission routes1
Has abstractyes

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