Tax Cryptographia: Exploring the Fiscal Design of Cryptocurrencies
Bibliographic record
Abstract
While the founders of cryptocurrencies may not conceptualize their efforts as such, the infrastructural choices they make in designing their systems mimic those routinely made by lawmakers in the design of fiscal policy. The totality of their decision-making in this regard constitutes essential elements of “taxation” written into the governance structure of the cryptocurrency system — its tax cryptographia . This article examines how cryptocurrency founders determine what common goods are necessary to make their systems viable and then design a way to fund them. The object of comparing certain cryptographic design elements to taxation is to examine how investors, speculators, enthusiasts, and skeptics should assess the decisions that founders make, and why it might matter if the participants in cryptocurrency systems recognize the fiscal infrastructure as a reproduction of state-like functions that serve to allocate the cost and benefits of participating in the collective activity despite the core motivation of cryptocurrency to bypass centralized and hierarchical political institutions.
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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 | 0.000 | 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 | 0.001 | 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 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".