Crypto/Space: Computational parasitism, virtual land grabs, and the production of Web3 Exit zones
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper explores how so-called ‘Web3’ blockchain projects are materially and socially constituted. A blockchain is an append-only distributed database. The technology is being hyped as applicable for a whole range of industries, social service provisions, and as a fix for economic disparities in communities left behind by mainstream financial systems. Drawing on case studies from our ongoing research we explain how, despite being virtual, Web3 projects are dependent on clearly defined spaces of production from which they derive their speculative value. We conceptualise this relationship as Crypto/Space, where space and blockchain software are mutually constituted. We consider how Crypto/Spaces are produced in three ways: 1) how project developers are adopting a parasitic relationship with host locations to appropriate energy, infrastructure, and local resources; 2) how projects enable ‘virtual land grabs’ where developers are engaging in land acquisitions, and associated displacement of local people, with no real intention to use the land for the declared purpose; and 3) how blockchain technology and speculative finance imaginaries are inspiring new anarcho-capitalist crypto-utopian ‘Exit zones’, often in the Global South. Far from being a zero-sum virtual game world, we argue that cryptocurrency projects are parasitic, often requiring predation on poor and otherwise marginalised communities to appropriate resources, onboard new users and enable favourable regulation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it