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Record W2318504640 · doi:10.2118/0312-023-twa

Work/Life Balance in the 21st Century

2012· article· en· W2318504640 on OpenAlexaff
Jarrett Dragani

Bibliographic record

VenueThe Way Ahead · 2012
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsCenovus Energy (Canada)
Fundersnot available
KeywordsWork–life balanceWork (physics)Balance (ability)HappinessScope (computer science)ProductivityPublic relationsSociologyPsychologyMarketingBusinessPolitical scienceComputer scienceSocial psychologyEconomicsEconomic growthEngineering

Abstract

fetched live from OpenAlex

Soft Skills - A survey looking at work/life balance in the 21st century. Work to live, or live to work? Working hard, getting the job done, and having a fulfilled life at home—can we really have it all? In a globalized world where business never stops and nearly all our business tools enable constant communication, where do we draw the line between work and leisure? In addition, what impact does separation between work and leisure have on our performance, job satisfaction, and wellbeing? These intriguing questions were among those posed to participants in The Way Ahead’s global survey in an attempt to investigate and contrast work/life balances found in the oil and gas industry compared with other industries. The Concept of Work/Life Balance Work/life balance is a concept that significantly affects the health and happiness of one’s life. The concept rests on your agenda for demarcating the amount of time you spend with work and the amount of time you spend in leisurely pursuits, where leisure is everything outside the scope of your work. Work/life balance is an area of research dating back to the 1960s. In fact, it began as a topic of study in management as an attempt to formulate working conditions that maximized productivity for industrial companies. It has often been a theme of political and social discussion, and it is important to realize that different societies have different perceptions about what a suitable work/life balance is.

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 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 score0.316
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.078
GPT teacher head0.387
Teacher spread0.309 · 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

Citations3
Published2012
Admission routes1
Has abstractyes

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