Afterlives of the Californian Ideology| Building Blockchain Frontiers: Ethereum as an Extension of the Californian Ideology
Bibliographic record
Abstract
The Ethereum blockchain has emerged as a new technology with particular affordances that lend themselves to entrepreneurial visions aligned with the Californian Ideology. Conceptualizing Ethereum as “the world computer” offers a compelling vision for those inspired by the Californian Ideology. This article examines two case studies—talks presented at DevCon4, the Ethereum community’s largest annual conference—to investigate some of the physical prototypes fueled by a supposedly ethereal technology. We focus on two distinct framings of Ethereum: As part of Silicon Valley elite Stewart Brand’s long-term futurist vision and crypto millionaire Jeff Berns’s utopian community in the Nevada desert. Through an ethnographic analysis of their frontier-themed visions, we argue that Ethereum proponents strategically use elements of the Californian Ideology to situate themselves in a successful history that also blends commercial success with countercultural elements.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.018 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".