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Record W2907897447 · doi:10.5539/ibr.v12n1p110

The Role of Social Support on Job Burnout in the Apparel Firm

2018· article· en· W2907897447 on OpenAlexvenueno aff
Treshalin Sellar

Bibliographic record

VenueInternational Business Research · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsBurnoutContext (archaeology)ClothingPsychologyBusinessSocial supportDemographic economicsSocial psychologyClinical psychologyEconomicsPolitical science

Abstract

fetched live from OpenAlex

Managing the causes of job burnout has become a momentous phenomenon in career management literature. Majority of the apparel firms in Sri Lanka are experiencing job burnout as a massive dispute where it represents many work-related and non-work related issues that employees endure. In this context, the present study was conducted with the aim of investigating the impact of social support on job burnout among the female worker level employees of a leading apparel firm in Sri Lanka. The study is mainly considering the primary data. Present study is using survey method to analyze the objectives. The data were collected through a self-administrated questionnaire from 142 respondents of the selected apparel firm. The correlation analysis of the study revealed that the social support has a strong negative relationship with job burnout while regression analysis identified that social support is significantly contributing to determine job burnout (51.1%). Moreover, multiple regression analysis indicated that family support has the highest impact on job burnout among the worker level employees. The findings of the study have various managerial implications for other apparel manufacturing firms and other industries in Sri Lankan social context.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.362
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.349
Teacher spread0.310 · 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; both teacher heads agree on what is shown here.

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

Citations14
Published2018
Admission routes1
Has abstractyes

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