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Record W3012293822 · doi:10.1504/ijhrdm.2020.106257

Work-life conflict costs: a Canadian perspective

2020· article· en· W3012293822 on OpenAlexaboutno aff
Said Baadel, Stefane Kabene, Asim Majeed

Bibliographic record

VenueInternational Journal of Human Resources Development and Management · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsPerspective (graphical)Work (physics)BusinessManagementPublic relationsOperations managementPolitical scienceEconomicsComputer scienceEngineering

Abstract

fetched live from OpenAlex

With current trends showing increased work hours, dual-earner households, and less time spent with family, it is evident that there is a work-life conflict. It is important for human resource managers in Canada to adapt to this changing trend by implementing new policies and programs. Our goal was to discover if there was a correlation between the work-life conflict and absenteeism. Our research study demonstrated that there is no significant correlation between hours worked and time spent with family, but there is a positive significant relationship between time spent working and absenteeism. Our study also indicates a positive correlation between time spent with family and absenteeism. Canadian companies can ease the implications of work-life conflict by adopting some work-life best practices. These practices include reduced work hours and flexible schedules that are already prevalent in European countries.

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)0.001
metaresearch head score (Gemma)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.126
Threshold uncertainty score0.914

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.009
Science and technology studies0.0100.002
Scholarly communication0.0070.002
Open science0.0020.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0100.000

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 head0.042
GPT teacher head0.305
Teacher spread0.262 · 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".

Quick stats

Citations6
Published2020
Admission routes1
Has abstractyes

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