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Record W2726207870 · doi:10.1080/00380253.2016.1246905

Ironic Flexibility: When Normative Role Blurring Undermines the Benefits of Schedule Control

2016· article· en· W2726207870 on OpenAlexaff
Scott Schieman, Paul Glavin

Bibliographic record

VenueSociological Quarterly · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsNormativeFlexibility (engineering)Work–family conflictControl (management)Work scheduleScheduleJob satisfactionWork (physics)Social psychologyPsychologyWorkforcePolitical scienceEconomicsManagementLaw

Abstract

fetched live from OpenAlex

Schedule control is touted as a potent work-related resource that helps workers minimize work–family conflict and enhance their own well-being. We ask: Does normative role blurring undermine those benefits? Normative role blurring involves the perceived expectation in the workplace culture that workers should take work home during nonwork hours and/or days. Analyses of the 2002 National Study of the Changing Workforce (NSCW) demonstrates that normative role blurring undermines the benefits of schedule control for work–family conflict and multiple indicators of worker well-being: job satisfaction, turnover intentions, anxiety, and life satisfaction. Moreover, to varying degrees, work–family conflict contributes to those conditional effects on well-being. Our observations offer new insights about the challenges of normative role blurring in workplace cultures and their implications for the benefits of schedule control.

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)0.005
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.007
Scholarly communication0.0040.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.040
GPT teacher head0.297
Teacher spread0.257 · 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 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

Citations42
Published2016
Admission routes1
Has abstractyes

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