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Work–Life Interface and Flexibility: Impacts on Women, Men, Families, and Employers

2013· book-chapter· en· W2412934043 on OpenAlexaff
Alison M. Konrad

Bibliographic record

VenueOxford University Press eBooks · 2013
Typebook-chapter
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsWestern University
Fundersnot available
KeywordsFlexibility (engineering)Work (physics)Psychological resilienceBusinessInterface (matter)Public relationsKnowledge managementPsychologySocial psychologyPolitical scienceManagementEngineeringComputer scienceEconomics

Abstract

fetched live from OpenAlex

Abstract Traditional organizational cultures pressure workers to prioritize the paid work role and to sacrifice participation in other life domains. However, performance in the paid work role affects and is affected by other roles the worker considers important. Multiple roles often conflict, but they also create positive synergies whereby workers utilize skills, ideas, and resources gained in different domains to enhance performance in all of them. Supportive organizational cultures and work–life flexibility practices help workers manage the interface between paid work and other life domains, and evidence suggests that they enhance work attitudes and performance. Given that multiple roles enhance workers’ performance, commitment, and resilience, organizational structures and cultures that support employees’ participation in multiple life domains are likely to generate positive benefits for firms as well as employees. The chapter ends with a theoretical model intended to stimulate future research in this area.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0170.001

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 head0.037
GPT teacher head0.251
Teacher spread0.214 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations2
Published2013
Admission routes1
Has abstractyes

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