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Record W4405419301 · doi:10.1111/joca.12612

Does financial knowledge affect borrower discouragement among various social categories? Evidence from the United States

2024· article· en· W4405419301 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Consumer Affairs · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsUniversity of OttawaYork University
Fundersnot available
KeywordsAffect (linguistics)Race (biology)Demographic economicsFinanceBusinessEconomicsPsychologySociology

Abstract

fetched live from OpenAlex

Abstract A deficiency in financial knowledge often precipitates costly financial choices, affecting consumers' behavior and decision‐making. We delve into how financial acumen influences borrower discouragement by utilizing data from the U.S. Federal Reserve's Survey of Household Economics and Decision‐Making (2017–2022). Discouraged borrower describes creditworthy individuals who, despite a genuine need for credit, avoid applying due to anticipated rejection. Our research reveals that financial knowledge diminishes the likelihood of borrower discouragement after controlling for various societal groups. However, when we estimate the model separately, its impact is not uniform across these societal segments. Specifically, our study uncovers that the effects of financial knowledge are different on gender, race, and occupational status. Further analyses of various subgroups confirm that race and occupational status are consistent predictors of borrower discouragement, even when accounting for financial knowledge. These insights underscore the importance of providing targeted financial education to address these disparities.

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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.200
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.259
Teacher spread0.244 · 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