MétaCan
Menu
Back to cohort
Record W2985841316 · doi:10.1108/pr-01-2019-0048

Workplace flexibility and its relationship with work-interferes-with-family

2019· article· en· W2985841316 on OpenAlexaff
Michael Halinski, Linda Duxbury

Bibliographic record

VenuePersonnel Review · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsCarleton UniversityToronto Metropolitan University
Fundersnot available
KeywordsFlexibility (engineering)OriginalityPsychologyConstruct (python library)Coping (psychology)Structural equation modelingSocial psychologyKnowledge managementComputer scienceManagement

Abstract

fetched live from OpenAlex

Purpose Drawing from the workplace flexibility and coping literatures, the purpose of this paper is to re-conceptualize the workplace flexibility construct as a coping resource that may help prevent work-interferes-with-family (WIF) from arising and/or assist employees manage such interference when it has occurred. A measure capturing this re-conceptualized view of flexibility is developed and tested using two samples of dual-income employees with dependent care demands. Design/methodology/approach In Study 1, the authors use LISERL to develop and test a new multi-dimensional measure of workplace flexibility ( n 1 =6,659). In Study 2 ( n 2 =947), the authors use partial least squares, a component-based structural equation modeling technique, to test a model that posits workplace flexibility that helps employees cope with WIF. Findings This research provides support for the idea that workplace flexibility helps employees cope with WIF by: preventing interference (i.e. negatively moderating the relationship between work hours and WIF), and managing interference that has occurred (i.e. negatively moderating relationship between WIF and perceived stress). Originality/value This study highlights the complexity of the relationship between workplace flexibility and work-to-family interference and offers guidelines on how employers and employees can use the workplace flexibility measure developed in this study.

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)0.000
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 score0.329
Threshold uncertainty score0.595

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
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 head0.061
GPT teacher head0.317
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.

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

Citations21
Published2019
Admission routes1
Has abstractyes

Explore more

Same venuePersonnel ReviewSame topicWork-Family Balance ChallengesFrench-language works237,207