COVID-19 Hasn’t Killed Merchant Acceptance of Cash: Results from the 2023 Merchant Acceptance Survey
Bibliographic record
Abstract
In recent years, the rise in digital payments has spurred a discussion in Canada and other countries about the future of cash at the point of sale. To better understand trends in payment methods accepted by Canadian businesses, including cash acceptance and the impact of innovations such as mobile payments, the Bank of Canada conducts the Merchant Acceptance Survey, a survey of small and medium-sized businesses. We find that 96% of these businesses in Canada accepted cash in 2023. Acceptance of debit and credit cards has increased since 2021 to 89%, and acceptance of digital payments has increased as well. However, the vast majority of merchants (92%) have no plans to go cashless in the future. Therefore, cash and digital payments continue to coexist at the point of sale, and Canada is far from being a cashless society.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".