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Record W3203861525

Organisational Work Pressure Rings a 'Time-Out' Alarm for Children: A Dual-Career Couple’s Study

2014· article· en· W3203861525 on OpenAlexaboutno aff
Gurvinder Kaur, Raj Kumar

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsAbsenteeismWorkforceWork (physics)Likert scalePsychologyScale (ratio)Social psychologyDemographic economicsDevelopmental psychologyPolitical scienceEngineering
DOInot available

Abstract

fetched live from OpenAlex

With the considerable increase of women’s share in workforce in all types of organisations and levels, their work and non-work demand has also increased. Therefore, dual career couples always faces new work-life challenges and a spill over effect on work and family demands. Their parenting role also got diverted to work demands due to increased organisational work pressure. However, new parents are even more occupied and restless as both of them are at the beginning phase of their career, perhaps getting less time to pay attention to their kids. This study is an empirical research on dual career couple. Data is being collected from various countries like India, USA, Canada, Australia and a sample of 70 working couples are taken. A questionnaire was framed, using a 5-point likert scale, consisting of 40 statements. The Cronback’s Alpha came out to be .80. Chi –square analysis technique has been used to show that there is a significant association between the organisational work pressure and age of children. This study provides the evidence that young parents, whose children age are under 2, always miss quality time with their children due the increased work pressure and stress and not able to manage time for them. This always results into high absenteeism, turnover and less organisational commitment. The results are discussed from variable children’s age perspective. Also implications of these findings are presented.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.279
Teacher spread0.256 · 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.

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

Citations5
Published2014
Admission routes1
Has abstractyes

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