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Record W4306648038 · doi:10.1080/07393148.2022.2129924

Good Short-Time Work for All

2022· article· en· W4306648038 on OpenAlexaff
Tom Malleson

Bibliographic record

VenueNew Political Science · 2022
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsThe King's UniversityWestern University
Fundersnot available
KeywordsWork (physics)AutonomyState (computer science)Order (exchange)Economic JusticeLaw and economicsQuality (philosophy)SustainabilityPublic relationsSociologyBusinessPolitical scienceLawComputer scienceEngineering

Abstract

fetched live from OpenAlex

Abstract This paper advances three arguments. First, current working-time patterns are destructive of justice, especially in terms of environmental sustainability, gender equality, and personal autonomy. Second, making fundamental progress towards these goals requires secure, quality, short-time work for all. This refers to an economic system that would guarantee everyone a decent, secure, existence at roughly 30 hours or less of market work, as well as actively discouraging longer hours. This discouragement should take the form of “soft” state policies as well as new cultural norms; it should not take “hard” forms of state violence. Third, liberal proceduralists are wrong to believe that individuals should be free from state regulation to simply choose the amount of work/leisure that they see fit, since doing so creates all kinds of harms for other people. In fact, the state should actively disincentivize long work hours in order to augment social justice.

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)0.007
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: Empirical · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.007
Scholarly communication0.0040.003
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0260.006

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 head0.099
GPT teacher head0.453
Teacher spread0.354 · 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
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

Citations3
Published2022
Admission routes1
Has abstractyes

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