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Record W2037117942 · doi:10.3138/cpp.36.3.287

The Declining Retirement Prospects of Immigrant Men

2010· article· en· W2037117942 on OpenAlexaffvenueabout
Derek Hum, Wayne Simpson

Bibliographic record

VenueCanadian Public Policy · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsPensionEarningsImmigrationPrivate pensionDemographic economicsEconomicsLabour economicsPolitical scienceFinance

Abstract

fetched live from OpenAlex

We compare the retirement prospects of immigrant men with their native-born counterparts. Using data from the Survey of Labour and Income Dynamics, we estimate a significant gap of 43 percent in private pension income and 30 percent in private pension contributions between immigrants and the native born. The gap in public pension incomes is negligible and reduces the overall pension gap, but only partially. Furthermore, the pension income and contribution gap is significantly larger for more recently arrived immigrant cohorts, consistent with evidence of weaker earnings for this group. We provide age profiles of pension income and contributions and discuss problems in interpreting the results without adjusting for age. Controlling for age and earnings differences, immigrants are still about 11 percent less likely to make contributions to a private pension program, but there is no difference in the contribution rates out of earnings of those who contribute. Recently arrived immigrants are significantly less likely to make contributions to a private pension program and appear to be neglecting private pension contribution opportunities more than earlier immigrants and the native born, which may have adverse implications for Canada's public retirement programs.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.912
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.132
GPT teacher head0.403
Teacher spread0.271 · 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 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

Citations16
Published2010
Admission routes3
Has abstractyes

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