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Record W2920977169 · doi:10.25071/1705-1436.99

Union Strategies to Re-Regulate Working Time

2006· article· en· W2920977169 on OpenAlexvenueno aff
Mark Thomas

Bibliographic record

VenueJust Labour · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsnot available
Fundersnot available
KeywordsWorking timeFlexibility (engineering)Collective bargainingWork (physics)InequalityWorking hoursWorking lifeWorking groupPart-time employmentQuality of working lifePublic relationsPolitical scienceLabour economicsSociologyEconomicsPsychologySocial psychologyManagementLawJob satisfactionEngineering

Abstract

fetched live from OpenAlex

The organization of working time is a central concern in today's labour market, as it is connected to experiences of work-life conflict, employment insecurity, and broader patterns of gender inequality. This article examines union responses to working time changes using a case study of four large unions, as well as a larger survey of working time provisions in major collective agreements. The article contends that working time re-regulation strategies include not only efforts to reduce hours of work, but also a range of strategies to promote 'employee-oriented time flexibility.' These working time strategies provide some means to address growing forms of work-life conflict and working time inequalities; however, these strategies are constrained by a number of factors, including employer resistance and the need for broader-based representational and collective bargaining structures.

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)0.008
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0030.002
Open science0.0020.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.018
GPT teacher head0.289
Teacher spread0.271 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2006
Admission routes1
Has abstractyes

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