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Record W2314836456

Quel impact la fiscalité québécoise a-t-elle sur les incitations au travail ?

2015· article· fr· W2314836456 on OpenAlexaboutno aff
Arnaud Blancquaert, Nicholas‐James Clavet, Jean‐Yves Duclos, Bernard Fortin, Steeve Marchand

Bibliographic record

VenueCahiers de recherche · 2015
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesArt
DOInot available

Abstract

fetched live from OpenAlex

Cet article présente un portrait des taux marginaux effectifs d’imposition (TMEI)et des taux d’imposition à la participation (PTR) sur le revenu de travail au Québec et en Ontario, de manière à mieux comprendre l’impact de la fiscalité et des transferts sociaux sur le comportement des agents, entre autres choses sur le marché du travail. Le système québécois, relativement au système ontarien, engendre des TMEI et des PTR élevés attribuables à la réduction généralement rapide des transferts avec le revenu de travail. Les TMEI québécois sont particulièrement élevés et variables entre 0 et 50 000$. Le TMEI des familles biparentales aux revenus d’environ 20000$ dépasse même les 125% ; 40% de ces familles biparentales font face à un TMEI qui dépasse 50%. La moyenne des PTR dans l’ensemble de la population est de 41%. Par ailleurs, une meilleure intégration des système fiscal et de transferts résulterait en une plus grande transparence, de meilleurs effets redistributifs et en une plus grande efficacité administrative et économique du système fiscal et de transferts.

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)0.001
metaresearch head score (Gemma)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.158

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0170.001

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 head0.273
GPT teacher head0.423
Teacher spread0.150 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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