A Survey of the Accounting Industry on Holdings of Cryptocurrencies in Xiamen City, China
Bibliographic record
Abstract
This is the first survey conducted in China on the holding of cryptocurrencies. Although cryptocurrencies have existed in the world for more than a decade, because the exchange of cryptocurrencies is banned in China, there is no guidance on the holding of cryptocurrencies in China’s accounting standards. Moreover, although the exchange of cryptocurrencies is prohibited by the Chinese government, holdings of cryptocurrencies by Chinese entities and individuals cannot be prevented. Thus, we conducted a survey in investors’ attitudes towards cryptocurrencies in Xiamen City, a special economic zone (SEZ) and a pilot free trade zone (FTZ) in China. The survey respondents commonly defined cryptocurrencies as investments (45%), inventories (19%), and intangible assets (36%). A total of 84% of respondents stated that the value of a cryptocurrency should be represented by a fair value. These results are similar to those obtained in a survey by The Digital Assets Accounting Consortium (DAAC), but different to the tentative agenda decision of the International Financial Reporting Standards Interpretations Committee (IFRSIC). Additionally, 65% of respondents stated that they prefer to accept cryptocurrencies as cash equivalent currencies, and these cash equivalent currencies were considered to have two main functions: a medium of exchange (56%) and a monetary unit for pricing goods and services (52%).
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".