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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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.018
Scholarly communication0.0070.006
Open science0.0000.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0100.000

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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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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