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Record W4206917892 · doi:10.1111/emre.12502

Pandemic fears, family interference with work, and organizational citizenship behavior: Buffering role of work‐related goal congruence

2022· article· en· W4206917892 on OpenAlexaff
Dirk De Clercq, Renato Pereira

Bibliographic record

VenueEuropean Management Review · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsBrock University
Fundersnot available
KeywordsPsychologyOrganizational citizenship behaviorSocial psychologyModerationModerated mediationTelecommutingWork (physics)MediationCongruence (geometry)CitizenshipOrganizational commitmentWork–family conflictSurvey data collectionPublic relationsSociologyPolitical science

Abstract

fetched live from OpenAlex

Abstract Pandemic fears are nearly inescapable, with likely effects on organizational citizenship behavior. This article considers the potential mediating influence that arises if employees experience family interference in their work, as well as the potential buffering role of work‐related goal congruence, in this relationship. Survey data were collected from employees who work in the information technology (IT) consulting sector in Portugal. The research hypotheses were tested with a bootstrapping approach, based on the Process macro, which enables the simultaneous assessment of mediation and moderation effects. The empirical results show that employees' ruminations about the coronavirus diminish their voluntary work behaviors, because their family‐related stress interferes with their work. Such harmful outcomes are less prominent among employees who perceive work‐related problems as mutually shared. This study accordingly reveals how organizations can limit the detrimental effects of the COVID‐19 pandemic by aligning the work‐related goals of their employee bases.

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)0.008
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 score0.003
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.014
GPT teacher head0.212
Teacher spread0.197 · 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

Citations15
Published2022
Admission routes1
Has abstractyes

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