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Record W12188687 · doi:10.17705/1cais.01508

www.Betfair.com: World-Wide Wagering

2005· article· en· W12188687 on OpenAlexaff
Daniel Shapiro, Leyland Pitt, Richard T. Watson

Bibliographic record

VenueCommunications of the Association for Information Systems · 2005
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsSimon Fraser University
FundersUniversity of Pittsburgh
KeywordsBusinessThe InternetMarketingValue (mathematics)Customer valueAdvertisingIndustrial organizationComputer scienceEconomicsMicroeconomicsWorld Wide Web

Abstract

fetched live from OpenAlex

Many industries are being fundamentally changed as entrepreneurs discover how to use the Internet to create higher customer value. Betfair has turned the gaming industry upside down with its exchange for gamblers. It has found a very efficient and effective way to match those who want to make and take bets, and also made these gamblers 10 percent better off compared to betting via traditional channels. The case describes the development of Betfair, its business model, and addresses the problems it faces as it expands beyond the boundaries of the United Kingdom.

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)0.001
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: none
Teacher disagreement score0.928
Threshold uncertainty score0.541

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.091
GPT teacher head0.376
Teacher spread0.284 · 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

Citations2
Published2005
Admission routes1
Has abstractyes

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