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Record W3125594171

Working Time Regulation, Unequal Lifetimes and Fairness

2016· article· en· W3125594171 on OpenAlexaff
Maxime Leroux, Grégory Ponthière

Bibliographic record

VenueSSRN Electronic Journal · 2016
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsEarningsInequalityEconomicsWorking timeArgument (complex analysis)Constant (computer programming)WageLabour economicsDecentralizationWorking hoursDemographic economicsMathematicsComputer scienceEngineeringWork (physics)Market economy
DOInot available

Abstract

fetched live from OpenAlex

We examine the redistributive impact of working time regulations in an economy with unequal lifetimes. It is shown that uniform working time reductions, when uncompensated (i.e. constant hourly wage), can reduce inequalities in realized lifetime well-being between short-lived and long-lived persons with respect to the laissez-faire, but at the cost of making the short-lived worse off. When compensated (i.e. constant labour earnings), uniform working time reductions make the short-lived better off, but at the cost of raising inequalities. Then, we characterize the ex post egalitarian optimum, where the realized lifetime well-being of the worst off is maximized, and show that this social optimum involves an increasing age profile in terms of worked hours. We examine the decentralization of that social optimum, and we provide a second-best egalitarian argument for age-dependent working time regulation, which can make the short-lived better off and reduce inequalities in realized lifetime well-being.

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)0.002
metaresearch head score (Gemma)0.004
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: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.020
GPT teacher head0.358
Teacher spread0.338 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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