Bibliographic record
Abstract
Although it is still in early stages, many commentators have been quick to note the revolutionary potential of next-generation or Bitcoin 2.0 technology. While some have expressed fear that the widespread application of these technologies may engender the rise of a Terminator-style Skynet, others believe that it represents the coming of a decentralized autonomous society (DAS) in which humans are freed from centralized forms of power through the proliferation of distributed autonomous organizations or DAOs. Influenced by neoliberal theory that stresses privatization, open markets, and deregulation, Bitcoin 2.0 technologies are implicitly working on the assumption that 'freedom' means freedom from the state. This neglects, however, that within capitalist societies, the state can also provide freedom from the vagaries of the market by protecting certain things from commodification. Through an analysis of (1) class and the role of the state; (2) the concentration and centralization of capital; and (3) the role of automation, I argue that the vision of freedom that underpins Bitcoin 2.0 tech is one that neglects the power that capital holds over us in both organizing the structure of our lives, and informing our idea of what it means to be human. In neglecting these other forms of power, I claim that the DAS might be a far more dystopian development than its supporters comprehend, making possible societies that are commodities all the way down.
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.
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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.045 |
| Scholarly communication | 0.012 | 0.014 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.012 | 0.012 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".