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Measuring Work—Life Interaction: The Australian Work and Life Index (AWALI) 2007

2008· article· en· W1985870137 on OpenAlexaboutno aff
Barbara Pocock, Natalie Skinner, Philippa Williams

Bibliographic record

VenueLabour & Industry a journal of the social and economic relations of work · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsWork (physics)Quarter (Canadian coin)Index (typography)Paid workPsychologyGerontologySocial psychologySociologyDemographic economicsMedicineGeographyEngineeringEconomics

Abstract

fetched live from OpenAlex

ABSTRACT The relationship between work and life is increasingly on the agenda of public and political debate in many industrialised countries. This article introduces a new measure of work-to-life interaction, the Australian Work and Life Index (AWALI). The article sets out the conceptual underpinnings of AWALI and the methods used to collect it, and presents selected findings from the 2007 data collection. It examines who is likely to experience worse work-life conflict, who seeks to change their working hours, and work-life outcomes for the self-employed. We find that a significant proportion of working Australians experience frequent work-to-life conflict: one-fifth to one-quarter of employees and self-employed workers. Groups at particular risk are men, parents (particularly fathers), and workers in professional or management occupations. Around 40 per cent of those surveyed would prefer to work fewer hours, and almost one-third of full-time women would prefer fewer hours. These findings indicate that work significantly affects workers' lives beyond the workplace, and that many Australians are working hours that they would like to change, even taking into account the effect on income. Furthermore, around twenty per cent of men (seventeen per cent of women) report that work frequently interferes with their community connections, indicating that work is having important effects on social connections, with unknown and unmeasured consequences for the strength of Australia's social fabric.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
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 studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.076
GPT teacher head0.294
Teacher spread0.218 · 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

Citations15
Published2008
Admission routes1
Has abstractyes

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