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Record W2011868962 · doi:10.7202/601005ar

Sur l’impact de l’assurance-chômage dans une économie keynésienne : On the impact of unemployment insurance in a Keynesian economy

2009· article· en· W2011868962 on OpenAlexaffvenue
Nguyễn Mạnh Hùng, Pierre Lefèbvre

Bibliographic record

VenueL Actualité économique · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Theory and Policy
Canadian institutionsUniversité du Québec à MontréalUniversité Laval
Fundersnot available
KeywordsDisequilibriumUnemploymentEconomicsKeynesian economicsFull employmentOrder (exchange)MacroeconomicsWelfare economicsFinance

Abstract

fetched live from OpenAlex

This paper deals with involuntary unemployment. We suppose that wages fail to clear markets and undertake a disequilibrium analysis of the effect of unemployment insurance (U.I.) on unemployment and production. The disequilibrium model is so constructed as to take into account the impact of U.I. on all markets. The neo-classical paradigm based on an equilibrium approach is contrasted with the neo-keynesian paradigm which assumes persistent disequilibrium. It is shown in this perspective that U.I. has an impact on unemployment when the latter is keynesian in nature rather than classical. We conclude that in order to evaluate empirically the effect of U.I., the various kinds of unemployment under analysis must be distinguished. We find moreover, that a disequilibrium framework is most appropriate for the study of unemployment.

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)0.003
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.000

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 head0.035
GPT teacher head0.255
Teacher spread0.221 · 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 designTheoretical or conceptual
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
Published2009
Admission routes2
Has abstractyes

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