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Record W1599635291

The Diversification and the Privatization of the Sources of Retirement Income in Canada

2006· preprint· en· W1599635291 on OpenAlexaboutno aff
Long Mo, Jacques Légaré, Leroy O. Stone

Bibliographic record

VenueRePEc: Research Papers in Economics · 2006
Typepreprint
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTransfer paymentDiversification (marketing strategy)PensionPopulationOrder (exchange)Labour economicsEconomicsPopulation ageingRevenueContext (archaeology)Private pensionIncome distributionDemographic economicsBusinessWelfareInequalityGeographyFinanceMarket economy
DOInot available

Abstract

fetched live from OpenAlex

Recent labour market developments in the context of population ageing have generated many changes concerning sources of retirement income. More precisely, this paper, which is based on two Statistics Canada surveys (Survey of Consumer Finances and Survey of Labour and Income Dynamics, ) will look at the processes of diversification and privatisation of income sources of Canada’s retirees during the period 1980-2002. This study has used the concept of individualized income based on the economic family in order to consider economies of scale and revenue sharing. An appropriate assessment of the composition of retirement income sources has been realized, while discerning five distinct categories: net government transfer payments, CPP/QPP benefits, private pensions, investment income and employment income. The situation of older women living alone and of older immigrants has been more carefully analyzed in order to detect some particularities among those two vulnerable groups. The results of this study demonstrate that retirees’ income composition has undergone many changes. In addition, sources of retirement income have become substantially more diversified and privatized during the period under study. These adjustments are becoming essential in western societies in order to overcome the obstacles caused by population ageing that could disrupt pension systems.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.077
Threshold uncertainty score0.382

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.277
Teacher spread0.258 · 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 teacher head, 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

Citations1
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueRePEc: Research Papers in EconomicsSame topicMigration, Aging, and Tourism StudiesFrench-language works237,207