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Record W2168021399 · doi:10.5539/ijef.v6n9p95

Observation of Financial Literacy among the Selected Students in the U.S. and Japan

2014· article· en· W2168021399 on OpenAlexvenueno aff
Kenichiro Chinen, Hideki Endo

Bibliographic record

VenueInternational Journal of Economics and Finance · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsnot available
FundersJapan Society for the Promotion of Science
KeywordsFinancial literacyTest (biology)PsychologyFinanceLiteracyMedical educationPedagogyBusinessMedicine

Abstract

fetched live from OpenAlex

This study examined the level of financial literacy and confidence in making own financial decisions college students in US and Japan. A total of 575 undergraduate students, 359 undergraduate students in Sacramento, the state capitol of California, and 216 undergraduate students in Aichi prefecture, located near the center of the Japanese main island, participated in this study. Financial literacy was measured by two instruments: Survey of Personal Financial Literacy Among College Students in Jump$tart and the three questions developed by Lusardi and Mitchell. The US collegiate students selected for this study demonstrated a better understanding of financial literacy compared to Japanese counterparts in both measurement instruments. Nearly a half of Japanese students in this study did not feel that they were ready to make their own financial decisions. Their lack of confidence in making financial decision was regrettably reflected on their poor performance in the financial literacy test. These findings highlight the need for a wholistic approach to financial education in Japan.

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)0.000
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 score0.022
Threshold uncertainty score0.209

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.010
GPT teacher head0.227
Teacher spread0.217 · 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

Citations8
Published2014
Admission routes1
Has abstractyes

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