MétaCan
Menu
Back to cohort
Record W4213220544 · doi:10.1177/00197939221076134

Remote Work and Post-Bureaucracy: Unintended Consequences of Work Design for Gender Inequality

2022· article· en· W4213220544 on OpenAlexafffund
Kim de Laat

Bibliographic record

VenueIndustrial and Labor Relations Review · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsBrock University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsWork (physics)BureaucracyAgile software developmentWaterfallFlexibility (engineering)Unintended consequencesPublic relationsPsychologySocial psychologySociologyPolitical scienceEngineeringManagementGeographyEconomics

Abstract

fetched live from OpenAlex

= 84) working under two types of work design-a post-bureaucratic work design labeled "agile," and a bureaucratic work design labeled "waterfall"-are used to examine gendered patterns in the adoption of remote work. Interviews reveal an unintended consequence of the agile model: It promotes a physical orientation that induces on-site work. Agile is gender-inegalitarian, with more women than men working remotely despite its perceived unacceptability, and low numbers of employees working remotely overall. By contrast, workers within a waterfall work design express a digital orientation to work and feel empowered to work remotely. The waterfall model is associated with gender egalitarianism; most employees opt to work remotely, and men and women do so in even numbers. Findings suggest that when compared to the post-bureaucratic work design, the bureaucratic work design provides more flexibility. This article refines our understanding of barriers to remote work and provides a lens on the gender dynamics underlying work design.

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)0.008
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.003
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.185
GPT teacher head0.361
Teacher spread0.176 · 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

Citations26
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueIndustrial and Labor Relations ReviewSame topicWork-Family Balance ChallengesFrench-language works237,207