Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Bitcoin, digital currencies and FinTech have been the subject of vigorous discussion. There has, however, been limited empirical evidence of its adoption and usage. This paper proposes a methodology to collect a nationally representative sample via the Bitcoin Omnibus Survey (BTCOS) in order to track the ubiquity and usage of Bitcoin in Canada. The paper reveals that about 64 per cent of Canadians have heard of Bitcoin, but only 2.9 per cent own it. Awareness of Bitcoin is strongly associated with men, and those with college or university education; additionally, Bitcoin awareness is more concentrated among unemployed individuals. On the other hand, Bitcoin ownership is associated with younger age groups and a high school education. Furthermore, the current authors have constructed a test of Bitcoin characteristics to attempt to gauge the level of knowledge held by respondents who were aware of Bitcoin, including actual owners. Knowledge is positively correlated with Bitcoin adoption. This paper attempts to reconcile the difference in awareness and ownership by deconstructing the transaction and store-of-value motive for holding Bitcoin. The paper concludes with some suggestions to improve future digital currency surveys, in particular to achieve precise estimates from the hard-to-reach population of digital currency users.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it