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Record W2581671993 · doi:10.5430/jbar.v6n1p20

Working Hour and Intention to Have Children in Hong Kong Full-Time Workers

2017· article· en· W2581671993 on OpenAlexvenueno aff
Fanny Yuk Fun Young

Bibliographic record

VenueJournal of Business Administration Research · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsWorking hoursWorking timeWorking motherWorking memoryPsychologyWorking lifeLegislationWorking environmentBalance (ability)DemographyMedicineWork (physics)Developmental psychologyPolitical scienceCognitionPsychiatryEngineering

Abstract

fetched live from OpenAlex

This study investigated the working hour, work-life balance and intention to have children of full-time workers in a place without Standard Working Hour legislation and with very low birth rate, Hong Kong. Method used a questionnaire survey with 200 below 35, married, full-time workers. Results showed these workers had longer working hour (49.3 hours/week) than many other places in the World (40 hours/week). Most participants (around 70 percent) reported prolonged fatigue level, sleepiness and extreme tiredness and did not have time staying with their partner and family. The mean intention to have children score was 2.045 out of 5. Correlation analysis was performed between working hour and intention to have children. There exist an inverse relationship between working hour and intention to have children (r= - 0.779). A plotting of the working hour against intention to have children showed some linear relationship between the working hour and intention to have children. Therefore, in general the workers with longer working hour were having lower intention to have children. To conclude, workers in Hong Kong, without Standard Working Hour legislation, had long working hours, poor work-life balance and low intention to have children.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.050
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.110
GPT teacher head0.416
Teacher spread0.306 · 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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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