MétaCan
Menu
Back to cohort

Quebec young adults’ use of and knowledge of credit

2006· article· en· W1979421682 on OpenAlexafffundabout
Marie J. Lachance, Pierre Beaudoin, Jean Robitaille

Bibliographic record

VenueInternational Journal of Consumer Studies · 2006
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsUniversité Laval
FundersCanada Millennium Scholarship FoundationFoundation for Economic Education
KeywordsDebtSample (material)Young adultPsychologyBusinessCredit cardActuarial scienceFinanceDevelopmental psychology

Abstract

fetched live from OpenAlex

Abstract This research aimed to study young adults’ use of and knowledge of credit. A large representative sample of Quebec young adults aged 18–29 years participated in a telephone survey. Results reveal that their use of credit has increased remarkably over the last decade. The mean score on the credit knowledge scale used in this study is 49.4% for the entire group. Ordinary least squares (OLS) regression analysis show that credit knowledge is positively related to personal income, number of debts, amount of total debt, number of credit cards and favourable attitude towards credit and debts. Young adults reporting either personal experience or family and relatives as their main source of learning about personal finances were found to have a lower level of knowledge about credit in general than those reporting having learned of this subject from courses, the media or financial counsellors. The learning of basic knowledge about credit and personal finances, with stress on the sensible use of credit, should be part of the educational agenda for young consumers.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.079
Threshold uncertainty score0.158

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.027
GPT teacher head0.279
Teacher spread0.253 · 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 source (direct Gemma or distilled Codex), 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

Citations36
Published2006
Admission routes3
Has abstractyes

Explore more

Same venueInternational Journal of Consumer StudiesSame topicFinancial Literacy, Pension, Retirement AnalysisFrench-language works237,207