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Record W4285464826 · doi:10.32920/ryerson.14639733

A Framework for Investigating the Value of Public Wireless Networks

2021· preprint· en· W4285464826 on OpenAlexafffundabout
Catherine A. Middleton

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicICT Impact and Policies
Canadian institutionsToronto Metropolitan University
FundersInfrastructure Canada
KeywordsWireless networkTelecommunicationsBusinessWirelessBusiness modelPrivate networkPublic valueValue (mathematics)Regional sciencePublic administrationGeographyPolitical scienceComputer scienceMarketingComputer security

Abstract

fetched live from OpenAlex

This paper investigates the value of deploying municipal wireless network infrastructure. By Vos's (2007c) estimate, there are more than 400 such networks, either deployed or in development in the United States. Many other wireless networks are operational, or being rolled out in cities around the world, including Toronto, London, Bologna, Singapore, Taipei and Perth. Developed by municipal governments, private providers or public-private partnerships, these networks are intended to serve the connectivity needs of local residents, tourists and business travellers.

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)0.010
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: Methods · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0020.007
Scholarly communication0.0090.011
Open science0.0020.003
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0130.001

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 head0.043
GPT teacher head0.281
Teacher spread0.238 · 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
GenreMethods

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
Published2021
Admission routes3
Has abstractyes

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