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Record W4400234587 · doi:10.24926/jsepa.v2i1.5218

How Government-Backed Registered Retirement Savings Plans Impact Canadians’ Tax-Free Savings Account:

2024· article· en· W4400234587 on OpenAlexafffundabout
Gino Biaou, Étienne Charbonneau

Bibliographic record

VenueJournal of Social Equity and Public Administration · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsÉcole Nationale d'Administration Publique
FundersCanada Excellence Research Chairs, Government of Canada
KeywordsEquity (law)Government (linguistics)Social securitySavings accountFinancial inclusionPensionFinancial literacyEconomicsBusinessPublic economicsDemographic economicsFinanceActuarial scienceFinancial servicesPolitical science

Abstract

fetched live from OpenAlex

Personal savings can help cushion financial difficulties and reduce the need to apply for government assistance. This study examined who benefits the most and the least from the government-supported Registered Retirement Savings Plan (RRSP) and Tax-Free Savings Account (TFSA). The compound theory of social equity was used to analyze data from the 2019 Canadian Survey of Financial Security. The results suggest that there are disparities in contributions to TFSA and RRSP based on the level of education and gender of single parents. Our analysis using correlation, OLS, and quantile regressions found that there are statistically significant but relatively small differences in contributions for less educated individuals and single-parent families led by women. These findings suggest that governments could focus on financial education, improve financial inclusion policies, and review rules on TFSA and RRSP contribution limits, which could pose a cognitive administrative burden for vulnerable households.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.299
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0040.004
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 head0.035
GPT teacher head0.286
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 teacher head, not a consensus.

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

Citations1
Published2024
Admission routes3
Has abstractyes

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