Opportunities for digital assets in a fractured world
Bibliographic record
Abstract
The US dollar's dominance in international trade and finance is facing threats from increasingly fractured global economic and financial systems. The foundation of the US dollar, built on the American economy's strength in world trade, the liquidity of its financial markets and accessibility of US dollar assets, is beginning to crack. But options for digital assets that could replace the US dollar have their own challenges. Crypto-assets such as bitcoin are inherently unstable in their purchasing power, which makes them less than ideal for international transactions. Stablecoins are more stable, as their name implies, because they are linked to fiat currency (usually the US dollar). Although stablecoins are beginning to play a larger role in international transactions, they require close ties to the US financial system and a sound regulatory framework. Stablecoins would thus increase a jurisdiction's dependence on the United States. As a result, many countries are exploring central bank digital currencies as an alternative to both bitcoin and stablecoins to maintain their monetary sovereignty.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.015 | 0.019 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.095 | 0.023 |
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".