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Record W2171255022 · doi:10.3138/cpp.34.3.281

Improving the Labour Market Incentives of Canada's Public Pensions

2008· article· fr· W2171255022 on OpenAlexaffvenueabout
Kevin Milligan, Tammy Schirle

Bibliographic record

VenueCanadian Public Policy · 2008
Typearticle
Languagefr
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsWilfrid Laurier UniversityUniversity of British Columbia
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

Dans cet article, nous analysons les mesures incitatives à la retraite imposées par le régime de retraite public au Canada. Une série de stimulants illustrent les diverses composantes du régime de retraite qui motivent les Canadiens âgés à continuer de travailler ou qui, au contraire, les dissuadent de le faire. Nous montrons d’abord que les mesures de dissuasion les plus importantes sont reliées aux prestations fondées sur le revenu du Supplément de revenu garanti, qui, interagissant avec le Régime de pensions du Canada/Régime de rentes du Québec et avec le revenu gagné, fait que, pour les moins nantis, le choix de continuer à travailler est moins rentable sur le plan financier. Ensuite, nous illustrons comment diverses réformes des politiques pourraient atténuer certains aspects du problème des mesures incitatives, et éliminer partiellement les barrières qui démotivent les Canadiens âgés de continuer à participer au marché du travail.

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)0.014
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 score0.056
Threshold uncertainty score0.380

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.001
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0110.000

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 head0.131
GPT teacher head0.334
Teacher spread0.202 · 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

Citations18
Published2008
Admission routes3
Has abstractyes

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Same venueCanadian Public PolicySame topicRetirement, Disability, and EmploymentFrench-language works237,207