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Record W2147100389 · doi:10.1086/668406

Money Isn’t Everything, but It Helps If It Doesn’t Look Used: How the Physical Appearance of Money Influences Spending

2012· article· en· W2147100389 on OpenAlexaff
Fabrizio Di Muro, Theodore J. Noseworthy

Bibliographic record

VenueJournal of Consumer Research · 2012
Typearticle
Languageen
FieldNeuroscience
TopicPsychology of Moral and Emotional Judgment
Canadian institutionsUniversity of GuelphUniversity of Winnipeg
Fundersnot available
KeywordsPrideCurrencyContext (archaeology)EconomicsElectronic moneyMonetary economicsCommerceAdvertisingBusinessPaymentLawFinancePolitical scienceHistory

Abstract

fetched live from OpenAlex

Abstract Despite evidence that currency denomination can influence spending, researchers have yet to examine whether the physical appearance of money can do the same. This is important because smaller denomination bills tend to suffer greater wear than larger denomination bills. Using real money in the context of real purchases, this article demonstrates that the physical appearance of money can override the influence of denomination. The reason being, people want to rid themselves of worn bills because they are disgusted by the contamination from others, whereas people put a premium on crisp currency because they take pride in owning bills that can be spent around others. This suggests that the physical appearance of money matters more than traditionally thought, and like most things in life, it too is inextricably linked to the social context. The results suggest that money may be less fungible than people think.

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)0.001
metaresearch head score (Gemma)0.007
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 score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.264
GPT teacher head0.407
Teacher spread0.143 · 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

Citations94
Published2012
Admission routes1
Has abstractyes

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