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Record W4387696275 · doi:10.1007/s44206-023-00069-9

Cyber Micronations and Digital Sovereignty

2023· article· en· W4387696275 on OpenAlexaff
Harry Hobbs, Philip Hayward, Robert Motum

Bibliographic record

VenueDigital Society · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsUniversity of Toronto
FundersUniversity of Technology Sydney
KeywordsSovereigntyCyberspacePerformative utteranceCitizenshipState (computer science)The InternetPolitical scienceSociologyInternet privacyLawMedia studiesEpistemologyPoliticsWorld Wide WebComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

Abstract The Internet has spurred the development of thousands of virtual nations. Located entirely online, these micronations claim sovereignty over vast stretches of cyberspace and engage in performative rituals of statehood. They draft constitutions, compose national anthems, sell citizenship, and sometimes, confuse or confound ordinary people. What are these entities and why do their founders and proponents purport to be a state? What legal and ethical challenges do cyber micronations provoke, and how do they challenge orthodox conceptions of the state? This brief communication considers these questions.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.652
Threshold uncertainty score0.447

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.024
GPT teacher head0.296
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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