Benchmarking Bitcoin Adoption in Canada: Awareness, Ownership and Usage in 2018
Bibliographic record
Abstract
The Bank of Canada commissioned the Bitcoin Omnibus Survey in 2016 to monitor trends in the adoption and use of Bitcoin and other cryptoassets. This report presents findings from the latest iteration of the survey, which was conducted in 2018. We find that between 2016 and 2018 the share of Canadians who were aware of Bitcoin increased from 62 percent to 89 percent and those that owned Bitcoin increased from 3 percent to 5 percent. However, the share of past owners also increased, suggesting an influx of Bitcoin owners who subsequently divested after the steep rise of prices in 2017. The main reason for owning Bitcoin remains speculation, though this share decreased slightly since 2017. On the other hand, the share of Canadians who reported using Bitcoin for transactions a few times a month or more increased. Finally, we discuss how Bitcoin adopters differ from overall Canadians with respect to their financial literacy and cash holdings.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".