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Record W2945523991

Canadian Retirement Security: A New Reality of Low Returns

2013· preprint· en· W2945523991 on OpenAlexaboutno aff
Bonnie‐Jeanne MacDonald, Lars Osberg

Bibliographic record

VenueRePEc: Research Papers in Economics · 2013
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsInterest rateFinancial crisisPensionSocial securityPovertyStock marketPopulationFinancial marketPoverty rateBusinessDemographic economicsEconomicsFinanceEconomic growthGeographyMarket economyMedicine
DOInot available

Abstract

fetched live from OpenAlex

Using a population micro-simulation model, we compare the financial security of Canadian seniors in three scenarios: if Canadian financial markets (1) never experienced the financial crisis of 2008 (i.e. continued on their pre-2008 path); (2) experienced the crisis and recover in five years; or (3) enter a new long-term environment of depressed stock market growth and continued low interest rates. If recovery occurs, we project that the long-term effects of the financial crisis on retirement prospects will be the most felt by older workers now near retirement. If low interest rates continue, however, more severe repercussions await younger workers. Upper-income Canadians are affected the most by continuing low interest rates owing to their relatively greater holding of financial assets. Nevertheless, a long-term low interest rate environment will cause an additional 2.3% of Canadian seniors to experience poverty. Our results underline the vital role of the Canadian social pension program in both protecting poorer Canadian seniors from destitution, and in also shielding the lower, middle and even upper-income Canadian elderly population from financial market risk.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.136

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.030
GPT teacher head0.282
Teacher spread0.252 · 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 designNot applicable
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
Published2013
Admission routes1
Has abstractyes

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Same venueRePEc: Research Papers in EconomicsSame topicFinancial Literacy, Pension, Retirement AnalysisFrench-language works237,207