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Record W2979722491 · doi:10.5430/rwe.v10n3p147

Employees Aren’t Factory Slaves: Factors Determining Work Demand and Implications for HRM Practices

2019· article· en· W2979722491 on OpenAlexvenueno aff
Navaneethakrishnan Kengatharan

Bibliographic record

VenueResearch in World Economy · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsCollectivismContext (archaeology)Work (physics)Hofstede's cultural dimensions theoryFactory (object-oriented programming)Constraint (computer-aided design)SociologyHuman resource managementMarketingPublic relationsBusinessEconomicsManagementPolitical scienceSocial scienceGeographyEngineeringIndividualismLaw

Abstract

fetched live from OpenAlex

Although a plethora of studies on factors determining work demand have been investigated in the West, the Western findings cannot be directly applied to another cultural context and there is still rather constraint studies in collectivist cultural nations. Drawing on the conservation of resources theory and Hofstede’s cultural framework, the present study aims to fill a lacuna by identifying factors determining work demand in a collectivist cultural context. Anchored in ontological and epistemological assumptions, the study employed hypothetic-deductive approach with a survey strategy. Data were garnered from randomly selected 569 employees working in the banking sector with the aid of a self-administrated questionnaire. The results disclose that males work longer hours and experience greater work demand than females. The study further reveals the predictors of work demand: working hours had shown the largest impact, followed by tenure, gender, income, formal work-life policies and supervisory status. The present study questioned the worthiness of the equal policies for both men and women in the workplace and emphasised the needs for gender-based HR policies. On balance, the study pushes back the frontiers of work-family literature and becomes a springboard to future scholarly works.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.146
Threshold uncertainty score0.617

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.201
GPT teacher head0.445
Teacher spread0.244 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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