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Record W2534662991 · doi:10.1111/gwao.12146

Who Gets to ‘Work Hard, Play Hard’? Gendering the Work–Life Balance Rhetoric in Canadian Tech Companies

2016· article· en· W2534662991 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueGender Work and Organization · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsCarleton University
Fundersnot available
KeywordsWork–life balanceRealmScholarshipRhetoricWorkforceWork (physics)Public relationsInformation and Communications TechnologySociologyBalance (ability)Exploratory researchGender studiesPolitical sciencePsychologySocial science

Abstract

fetched live from OpenAlex

This article is based on an exploratory study of the implicit gender norms in work–life balance (WLB) rhetoric in ten Canadian information and communication technologies (ICT) organizations. Interviews with human resources (HR) managers and preliminary company website analysis revealed a masculinist and heterosexist bias in the implementation of WLB practices, legitimized by the gender composition of the workforce and the demanding yet inherently rewarding nature of the ICT sector. Participants deliberately separated care (read: childcare) from WLB (read: flexible hours and working from home), reproducing the assumption that an ‘ordinary’ worker is a man with a female partner who assumes primary responsibility for the reproductive realm. The study concludes with: (i) recommendations to increase HR's role in providing functional support for WLB practices and (ii) three future directions for research. This article contributes to a general call in feminist scholarship to apply a gendered lens to WLB practices.

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.

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 score0.070
Threshold uncertainty score0.942

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.028
GPT teacher head0.245
Teacher spread0.217 · 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