“If the news is fake, imagine history”: The network state and the second bourgeois revolution
Bibliographic record
Abstract
Written by Balaji Srinivasan (2022), founder of genetic testing firm Counsyl, former general partner at Andreesen Horowitz, and former CTO of Coinbase with close connections to anti-democratic tech billionaire Peter Thiel, The Network State imagines a new state form grounded in blockchain technology. After first situating text within longer genealogies of neoliberalism, authoritarian freedom, and libertarian exit, I then overturn the book’s central premise: that exit to the digital frontier via network states will increase human freedom. In highlighting how societies dominated by private property restrict human freedom by forcing the many to exchange their labour power to the few to survive, I argue that the creation of zones like the network state are instead a reflection of our epoch’s major dynamic: the attempt to shift the rights of capital and the authority over those rights to the transnational level. In contrast to those that see zones as part of an emerging neofeudalism, I conclude that The Network State is better understood as a legitimating text for a second bourgeois revolution.
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 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 | 0.002 | 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 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".