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Social Networks and Credit Card Overspending Among Young Adult Consumers

2012· article· en· W1969033565 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 · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsCredit cardDebtPerceptionChargebackBusinessSample (material)Credit card interestSocial network (sociolinguistics)ATM cardMarketingAdvertisingPsychologyFinanceSocial mediaPaymentPolitical science

Abstract

fetched live from OpenAlex

Research that has looked at the reasons why young individuals overspend using their credit cards has not paid attention to the perceptions that they have about important others' credit card debt, their expectations as to how much to spend when they consume in the presence of them, and how the strength of the social relationships within their social network potentially influences the extent to which they overspend using their credit cards. A survey of 225 US university students composing a culturally diverse sample revealed that these social norms and network variables have interactive effects on credit card overspending. Specifically, the results show that the perceptions that young adult consumers have about important others' credit card debt impact their overspending using credit cards when they feel that they are expected to consume at the same level as important others in shared experiences, and when they are strongly connected to these individuals.

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)0.000
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 score0.024
Threshold uncertainty score0.939

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.003
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 head0.011
GPT teacher head0.230
Teacher spread0.219 · 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