#buildbanksbetter: Central Bank Digital Currencies (CBDCs), Public Banks and Money’s Potential as a Non-Scarce Medium of Communication and a Source of Local Self-Determination
Bibliographic record
Abstract
This paper argues that public banking at the local and community level is the most effective monetary technology for restoring the powers of finance to the people. Public banking is not a new idea and it’s enjoying newfound popularity alongside the rise of modern monetary theory (MMT) and the emergence of a new generation of financially aware and digitally enabled researchers, “conspiracy theorists” and activists. So while these days cryptocurrencies are trumpeted as the cutting edge of alternative monetary technologies, I suggest that public banking is the money technology best able to respond to the democratic desires of today’s citizens. I conclude with a discussion of the development of Central Bank Digital Currencies (CBDCs) and the ways they are being used to undermine local, community-led self-determination by further centralizing monetary control in the centrally controlled system of central banks whose mandate is to serve private interests.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.343 | 0.117 |
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".