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Record W1798699069 · doi:10.1002/hrm.21549

Can Union Voice Make a Difference? The Effect of Union Citizenship Behavior on Employee Absence

2013· article· en· W1798699069 on OpenAlexaff
Stephen Deery, Roderick D. Iverson, Donna Maree Buttigieg, Christopher D. Zatzick

Bibliographic record

VenueHuman Resource Management · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsLoyaltyOrganizational citizenship behaviorCitizenshipCompetition (biology)AbsenteeismSocial psychologyBusinessPolitical sciencePublic relationsLabour economicsEconomicsPsychologyMarketingOrganizational commitmentLaw

Abstract

fetched live from OpenAlex

Abstract The interests of organizations and unions are often seen to be in competition. However, the union‐voice hypothesis suggests that unions can provide a distinctive mechanism to lower organizational costs by reducing exit behavior. This study looks at union citizenship behavior as a form of voice and examines its effect on employee absence. It draws on data from 367 branches of a large unionized banking organization to explore both the antecedents and outcomes of union citizenship behavior. Union citizenship behavior directed toward helping fellow members with workplace grievances was found to reduce branch‐level absenteeism, while union loyalty mediated the impact of a number of union‐related variables on union citizenship behavior. The implications for a balanced union‐management relationship are discussed in the article. © 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)0.003
metaresearch head score (Gemma)0.017
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 score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.020
GPT teacher head0.279
Teacher spread0.259 · 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

Citations30
Published2013
Admission routes1
Has abstractyes

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