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Record W4225327802 · doi:10.22215/clb20220301

The Canada Learning Bond, financial capability and tax-filing: Results from an online survey of low and modest income parents

2022· report· en· W4225327802 on OpenAlexafffundabout

Bibliographic record

Venuenot available
Typereport
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsCarleton University
FundersGovernment of Canada
KeywordsOutreachIncentiveBusinessDiversity (politics)PaymentTax creditBondDownloadPovertyEarned income tax creditWork (physics)Public economicsDemographic economicsFinanceActuarial scienceEconomicsEconomic growthPolitical science

Abstract

fetched live from OpenAlex

Previous research has identified several likely causes of eligible non-participation in the Canada Learning Bond (CLB), including awareness, financial exclusion, and administrative barriers. This study expands on that research, with a particular focus on the role of tax-filing as an administrative obstacle to accessing the CLB. I present results from an online survey of low and modest income parents (n=466) conducted in 2021. We find that, even among parents reporting they have received the CLB (46%), a majority (51%) report low confidence in their familiarity with the program, and more than one in six (17%) are unaware of the need to file tax returns to maintain eligibility for annual CLB payments. Self-reported regular tax-filing is associated with a 59% increase in the probability of accessing the CLB, even when controlling for a range of parental characteristics. This study confirms previous work by Harding and colleagues (2019) that non-filing may explain some share of eligible non-participation in education savings incentives. Tax-filing services may be an important pathway to improve CLB access. Low and modest income parents show substantial diversity in their preferred filing methods and outreach efforts cannot be concentrated in only one avenue if they are to be successful. The study also tests a small ‘nudge’ to address gaps in awareness and finds that information-only approaches to outreach are likely to have limited success, even with motivated populations.

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)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.042
GPT teacher head0.264
Teacher spread0.222 · 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 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
Published2022
Admission routes3
Has abstractyes

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