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Record W1518139746 · doi:10.1111/coep.12066

WHY IS CASH (STILL) SO ENTRENCHED? INSIGHTS FROM CANADIAN SHOPPING DIARIES

2014· article· en· W1518139746 on OpenAlexaffabout
Carlos Arango, Dylan Hogg, Alyssa Lee

Bibliographic record

VenueContemporary Economic Policy · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDigital Platforms and Economics
Canadian institutionsBank of Canada
Fundersnot available
KeywordsPaymentCashValue (mathematics)BusinessPayment service providerPayment cardEconomicsActuarial scienceCommerceFinanceComputer science

Abstract

fetched live from OpenAlex

One similarity among many developed economies is the predominance of cash over electronic payments in terms of payment frequency, especially for the low‐value transactions that are the bulk of retail payments. We use the Bank of Canada's 2009 Methods‐of‐Payment Survey, which collected information on consumers' payment choices through shopping diaries, to estimate a simple model of choice between cash and other payment methods. Results suggest that the main reasons cash is still a popular payment instrument in Canada, especially for low‐value transactions, are its wide acceptance among merchants compared with other alternatives, speed and ease of use, and low marginal cost when on hand. (JEL E41, D12, L81)

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)0.002
metaresearch head score (Gemma)0.013
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 score0.067
Threshold uncertainty score0.490

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.010
Science and technology studies0.0060.003
Scholarly communication0.0060.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.018
GPT teacher head0.194
Teacher spread0.176 · 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

Citations49
Published2014
Admission routes2
Has abstractyes

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