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Record W1515330203 · doi:10.1108/14636690310507207

The digital divide and the competitive behaviour of Internet backbone providers

2003· article· en· W1515330203 on OpenAlexaff
Daniel Roseman

Bibliographic record

VenueInfo · 2003
Typearticle
Languageen
FieldEngineering
TopicICT Impact and Policies
Canadian institutionsGolder Associates (Canada)
Fundersnot available
KeywordsThe InternetLiberalizationTelecommunicationsPaymentBusinessPlaintiffSubject (documents)Settlement (finance)Digital divideDeveloping countryInternet service providerPublic relationsInternet privacyEconomicsComputer scienceEconomic growthPolitical scienceFinanceMarket economyLawWorld Wide Web

Abstract

fetched live from OpenAlex

Against the background of international telecommunications liberalization and declining settlement payments for many developing countries, charging arrangements for Internet interconnection services (IIS) have become a controversial issue. Following on from the author’s article in the previous issue of info, which reviewed the complaints and counter‐arguments regarding whether current charging arrangements for Internet interconnection are inequitable and subject to anti‐competitive behaviour on the part of Internet backbone providers, this paper reviews proposals for action and makes a number of recommendations as to how to move the debate usefully forward, including a number of positive measures that developing countries can take themselves, as well as measures requiring cooperation among complainant and “complacent” countries.

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)0.004
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0040.012
Scholarly communication0.0100.007
Open science0.0000.004
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.006
GPT teacher head0.203
Teacher spread0.197 · 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 designObservational
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
Published2003
Admission routes1
Has abstractyes

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