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Record W2016104173 · doi:10.1108/17542411011026258

Managers, balance, and fulfilling lives

2010· article· en· W2016104173 on OpenAlexaff
Ronald J. Burke

Bibliographic record

VenueGender in Management An International Journal · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsYork University
Fundersnot available
KeywordsOriginalityContext (archaeology)Work (physics)Balance (ability)Value (mathematics)Personal lifePublic relationsWork–life balancePsychologySociologySocial psychologyPolitical scienceComputer scienceEngineering

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to provide a reflection on the author's earlier paper published in Gender in Management: An International Journal (formerly Women in Management Review ) in 2000 titled “Do managerial men benefit from organizational values supporting work‐personal life balance? Design/methodology/approach The paper is examined in the context of the author's research and writing program. Findings The 2000 paper built on the author's previous research and writing and informed their current research activities. In addition, the 2000 paper seemed to reflect emerging interest in work‐personal life balance or integration, as well as the experience of men at work, that was emerging at this time. Research limitations/implications Greater attention to the work and life experiences of men at work is warranted. Practical implications The paper finds that men benefit from organizational values supporting work‐personal balance as do other studies involving managerial and professional women. These collective findings suggest that organizations would benefit by supporting both male and female managers and professionals in their efforts to lead more complete lives as employees and family members. Originality/value The paper indicates that a greater understanding of men's lives would benefit not only men but also women and employing organizations.

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 score0.261
Threshold uncertainty score0.644

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.032
GPT teacher head0.325
Teacher spread0.293 · 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

Citations16
Published2010
Admission routes1
Has abstractyes

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