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Record W3000112035 · doi:10.7866/hpe-rpe.20.4.7

Canadian Gender Gap in Financial Literacy: Confidence Matters

2020· article· en· W3000112035 on OpenAlexfundaboutno aff
Raquel Fonseca, Simón Lord

Bibliographic record

VenueRevista Hacienda Pública Española · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaCanadian Institutes of Health Research
KeywordsFinancial literacyGender gapEconomicsFinanceDemographic economics

Abstract

fetched live from OpenAlex

We construct a financial literacy index as well as a financial confidence index in order to evaluate the effect of confidence on financial literacy, and more specifically, on the gender gap in financial literacy. Results confirm the existence of a gender gap in financial literacy in Canada, and show that having a higher con¬fidence in one’s financial skills and knowledge is indeed a factor that increases one’s financial literacy. Financial confidence is found not to track actual financial skills very closely across different ages, espe¬cially for women, and at older ages. We also find evidence that financial literacy and decision making are related to the relative education level of spouses. Using the Oaxaca-Blinder decomposition, confidence is also found to explain 14.15% of the gender gap in financial literacy, while being self-employed explains 19% of the gap, and taking part in the financial planning accounts for 16.76% of the gender gap difference. We find that most of the gap remains unexplained by differences in coefficients of men and women.

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 categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.752
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.029
GPT teacher head0.240
Teacher spread0.212 · 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; both teacher heads agree on what is shown here.

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

Citations20
Published2020
Admission routes2
Has abstractyes

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Same venueRevista Hacienda Pública EspañolaSame topicFinancial Literacy, Pension, Retirement AnalysisFrench-language works237,207