The 2021–22 Merchant Acceptance Survey Pilot Study
Bibliographic record
Abstract
In recent years, the rise in digital payment innovations such as contactless cards and Interac e-Transfer has spurred a discussion about the future of cash at the point of sale. The COVID19 pandemic has also contributed to this discussion: While consumers reported that some merchants started to refuse cash early in the pandemic, such reported refusals dropped as the pandemic progressed. The Bank of Canada’s most recent Merchant Acceptance Survey (MAS) took place in 2018, prompting a need for updated data to study merchant cash acceptance, payment trends and conditions for the potential issuance of a central bank digital currency (Lane 2020, 2021a). Against this background, the Bank conducted the 2021–22 MAS Pilot Study to monitor payment methods accepted by small and medium-sized businesses (SMBs). Survey data was collected from merchants in two batches, in late 2021 and early 2022. Our results show that 97% of SMBs in Canada accepted cash in 2021–22 and only 3% have plans to stop accepting cash. For cards and digital payments, merchant acceptance has increased since 2018. Additionally, the acceptance of different payment methods varies by the size of the merchant, industry and region.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".