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Record W4366569666 · doi:10.32721/ctj.2023.71.1.berger

"Tax-Free": The Effect of a Heuristic Cue on the Choice Between a TFSA and an RRSP

2023· article· en· W4366569666 on OpenAlexvenueaboutno aff
L. L. Berger, Jonathan Farrar, Ruth Pogacar, Lu Y. Zhang

Bibliographic record

VenueCanadian Tax Journal/Revue fiscale canadienne · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsHeuristicsHeuristicPreferenceEconomicsTax creditTerm (time)Public economicsPlan (archaeology)Test (biology)Actuarial scienceMicroeconomicsComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

The authors investigate whether and, if so, the extent to which a heuristic cue, the term "tax-free," contained in the name of one of the two primary tax-sheltered savings plans in Canada—the tax-free savings account (TFSA)—biases individuals' saving preferences relative to the registered retirement savings plan. On the basis of the heuristic-systematic model of information processing, the authors predict that the term "tax-free" is a favourable heuristic cue that will suppress systematic processing and bias individuals toward selecting a savings plan with this term in its name. They conduct three experiments to test this proposition. Overall, the results suggest that individuals have a clear preference for a tax-sheltered savings plan with "tax-free" in its name—regardless of the content of accompanying explanatory information. The preference for savings plans with "tax-free" in the name may suggest the need for more education and financial advice to reduce the use of heuristics.

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)0.003
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 score0.557
Threshold uncertainty score0.935

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.016
GPT teacher head0.214
Teacher spread0.198 · 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
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Tax Journal/Revue fiscale canadienneSame topicFinancial Literacy, Pension, Retirement AnalysisFrench-language works237,207