The Metaverse as the Digital Leviathan: A Case Study of Bit.Country
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
As Bitcoin continued to make headlines in 2021, additional digital assets such as non-fungible tokens brought more users into the blockchain ecosystem. As more individuals and entities took a closer look at the use cases for blockchain technology, the term metaverse began to emerge across news outlets and social media platforms. With Mark Zuckerberg, the Chief Executive Officer of Facebook, announcing that the organization would become a metaverse company and change the organization’s name to Meta, this announcement came with some criticism in that the Meta metaverse would be centralized. In this case study, the current state of nation-states was viewed through the lens of Hobbes’ The Leviathan to assess whether decentralized metaverses will transition to a Digital Leviathan using Bit.Country - a metaverse within the Polkadot blockchain ecosystem. The case study was conducted through interviews and uncovered that the quadruple bottom line implemented in conventional business could be transferrable to a digital world built on various blockchains, non-fungible tokens, and governance in a Digital Leviathan governed by the people.
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.
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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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