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Record W2493941103 · doi:10.5325/jinfopoli.3.2013.0411

Measuring Performance when Broadband is the New PSTN

2013· article· en· W2493941103 on OpenAlexaff
William Lehr, Steven Bauer, David D. Clark

Bibliographic record

VenueJournal of Information Policy · 2013
Typearticle
Languageen
FieldEngineering
TopicPower Line Communications and Noise
Canadian institutionsArtificial Intelligence in Medicine (Canada)
FundersNational Science Foundation
KeywordsBroadbandPublic switched telephone networkTelecommunicationsTelephone networkInternet accessThe InternetBroadband Integrated Services Digital NetworkBroadband networksBusinessComputer networkComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Abstract The transition of telecommunications services from the old Public Switched Telephone Network (PSTN) to the broadband Internet does not alleviate the needs of consumers for basic services. The Internet universe, however, is mostly unregulated. As broadband becomes the new PSTN, how do we ensure that services are delivered appropriately, and how can this be measured? Doctors Lehr, Bauer, and Clark propose an updated set of measurements and address the policy considerations they raise, in order to ensure that broadband services indeed serve the public interest.

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)0.005
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.017
GPT teacher head0.219
Teacher spread0.202 · 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 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

Citations12
Published2013
Admission routes1
Has abstractyes

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