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Record W4200491980 · doi:10.33423/jabe.v23i8.4874

Work-Family Conflict and Family Satisfaction: Evidence From Small Enterprise Managers

2021· article· en· W4200491980 on OpenAlexvenueno aff
Joseph Kwadwo Tuffour, Florence Mansa Bortey, Joseph Gerald Tetteh Nyanyofio

Bibliographic record

VenueJournal of Applied Business and Economics · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsWork (physics)Family resiliencePsychological resilienceWork–family conflictScale (ratio)PsychologyPsychological interventionSocial psychologyJob satisfactionFamily conflictGeographyEngineering

Abstract

fetched live from OpenAlex

The adult person is involved in managing family responsibilities and maintaining work activities on a daily basis. This creates conflict between work and family with implications for family satisfaction. Nonetheless, small-scale enterprises managers’ level of resilience could alter these implications. The objective of the study is to examine the effect of work-family conflicts on family satisfaction, by moderating the role of resilience. A cross-sectional design was applied to a sample of 293 managers. ANOVA results reveal that work-family conflict and family-work conflict are positive and significantly related but each has a significant negative relationship with family satisfaction. However, resilience positively and significantly moderates each of the effects of work-family and family-work conflicts on family satisfaction. Thus, increasing levels of the conflicts come with increasing levels of resilience to overcome work-family conflicts. This is the first study in Ghana to show that resilience has a significant role in mitigating the difficulties of work-family conflicts. It is recommended that policy-makers bring in resilience training interventions to reduce role conflicts and increase family satisfaction.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.346
Threshold uncertainty score0.610

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.038
GPT teacher head0.250
Teacher spread0.212 · 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 teacher head, 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

Citations3
Published2021
Admission routes1
Has abstractyes

Explore more

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