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IT firms' working time (de)regulation model: a by-product of risk management strategy and project-based work management

2013· article· en· W2752453579 on OpenAlexafffundabout
Marie‐Josée Legault

Bibliographic record

VenueWork Organisation Labour & Globalisation · 2013
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsUniversité du QuébecUniversité TÉLUQUniversité du Québec à Montréal
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsOvertimeWorkforceWork (physics)Product (mathematics)Unpaid workCapital (architecture)BusinessRisk managementLabour economicsEconomicsMarketingIndustrial organizationManagementEngineeringEconomic growth

Abstract

fetched live from OpenAlex

This paper, based on 140 interviews carried out in two case studies in Montreal over the past decade, builds on previous research results demonstrating the existence of unlimited unpaid overtime among videogame developers and software designers. It uses the two case studies to illustrate an emerging workplace regulation model based on unacknowledged unlimited and unpaid overtime. It argues that this model stems from the combination of information technology firms' risk management strategy with project-based working as an organisation mode and is closely tied to the high international mobility of both capital and workforce. This paper focuses just on the (de)regulation of working time, but it opens up a path to account theoretically for the (de)regulation of work more generally in an expanding sector of the workforce: ‘new professionals’ in knowledge work.

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)0.004
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.007
Scholarly communication0.0050.003
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.031
GPT teacher head0.287
Teacher spread0.256 · 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 designQualitative
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

Citations11
Published2013
Admission routes3
Has abstractyes

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