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Record W2108500195 · doi:10.24043/isj.294

Alderney: gambling, Bitcoin and the art of unorthodoxy

2014· article· en· W2108500195 on OpenAlexaffvenue
John Connell

Bibliographic record

VenueIsland Studies Journal · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicIsland Studies and Pacific Affairs
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsIngenuityThe InternetPopulationCreativityDisadvantagedBusinessResource (disambiguation)Raising (metalworking)Economic growthInternet privacyEconomicsPolitical scienceLawEngineeringSociologyComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Small islands are disadvantaged by conventional development strategies and have sought unusual means of achieving economic development and raising their global profiles. The small Channel Island of Alderney, with a largely non-existent physical resource base, and steady population decline, has sought to develop several service sector activities, increasingly involving the internet and virtual activities. Internet gambling has proved successful. Bitcoin minting offers unique possibilities. Alderney has achieved economic development without significant local assets other than creativity and ingenuity, and a somewhat distinctive political status.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0090.014
Scholarly communication0.0070.004
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0120.001

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 head0.042
GPT teacher head0.342
Teacher spread0.301 · 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 designQualitative
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

Citations5
Published2014
Admission routes2
Has abstractyes

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