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Record W1562624539

Remplacement du revenu familial pendant les annees de retraite : quels sont les resultats des Canadiens?

2010· preprint· fr· W1562624539 on OpenAlexaboutno aff
Sebastien Larochelle-Côté, John Myles, Garnett Picot

Bibliographic record

VenueRePEc: Research Papers in Economics · 2010
Typepreprint
Languagefr
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesArt
DOInot available

Abstract

fetched live from OpenAlex

Le present document vise a determiner dans quelle mesure le revenu familial gagne pendant les annees de travail est pendant les annees de retraite. A cette fin, on suit des cohortes au fur et a mesure qu'elles avancent en age, a partir du milieu de la cinquantaine jusqu'a la fin de leur septieme decennie de vie, en employant une source de donnees longitudinales fondee sur des dossiers fiscaux qui englobent 26 annees, de 1982 a 2007. Des travaux anterieurs des memes auteurs portaient sur cette question : ils avaient pour sujet les 50 % de la population ayant un niveau eleve de participation au marche du travail au milieu de la cinquantaine. Le present document prolonge ces travaux et inclut presque tous les Canadiens (80 % a 85 % de la population). Le revenu familial ajuste par equivalence dont dispose le Canadien a la fin de sa septieme decennie de vie represente environ 80 % de celui observe chez la meme personne au milieu de la cinquantaine (un taux de remplacement de 0,8). Les taux de remplacement a la retraite comportent une correlation negative avec le revenu gagne autour de l'age de 55 ans. Les taux medians de remplacement sont de 1,1 chez les personnes du quintile de revenu inferieur, de 0,75 dans le quintile intermediaire, et de 0,7 dans le quintile superieur. A la retraite, les regimes de pension publics et les autres transferts largement les gains et les autres revenus des personnes du quintile inferieur. Toutefois, certaines personnes ont des taux de remplacement tres faibles. Par exemple, 20 % des personnes du quintile de revenu intermediaire avaient des taux de remplacement inferieurs a 0,6. Les cohortes plus recentes avaient des revenus familiaux plus eleves a la retraite que les cohortes anterieures, par suite des gains et des revenus tires de regimes de pension prives plus eleves.

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)0.006
metaresearch head score (Gemma)0.027
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 score0.852
Threshold uncertainty score0.294

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.027
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.172
GPT teacher head0.408
Teacher spread0.236 · 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".

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Citations0
Published2010
Admission routes1
Has abstractyes

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Same venueRePEc: Research Papers in EconomicsSame topicRetirement, Disability, and EmploymentFrench-language works237,207