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Record W2273553870

A Desiderata for Wireless Broadband Networks in the Public Interest

2007· article· en· W2273553870 on OpenAlexaffabout
Amelia Bryne Potter, Andrew Clement

Bibliographic record

VenueSSRN Electronic Journal · 2007
Typearticle
Languageen
FieldEngineering
TopicICT Impact and Policies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPublic interestGeneral partnershipThe InternetBroadbandLegislationPublic sectorTelecommunicationsWireless broadbandBroadband networksInternet accessBusinessPublic domainPrivate sectorPublic–private partnershipPublic relationsWirelessEngineeringWireless networkPolitical scienceComputer scienceFinanceLaw
DOInot available

Abstract

fetched live from OpenAlex

There is currently an expanding range of initiatives in North America, and world-wide, attempting in various ways to develop public internet infrastructures. Discussion about them so far has concentrated on the benefits they espouse (bridge the digital divide, promote commerce,..), what technological configuration is best (e.g. WiFi, fiber, hybrids of these,..) and who should own (and perhaps build) them (e.g. private sector, public sector, or a partnership of these,...). What has been relatively absent to date is systematic analysis of the functional and performance characteristics of the infrastructure itself. Such an analysis would be invaluable in assessing the competing claims about such benefits, technologies and ownership models. This paper offers an analytic framework for assessing public internet infrastructures. Drawing initially on familiar criteria for communications infrastructures (e.g. ‘public interest, convenience and necessity’ from longstanding US public utility law, ‘universal and affordable’ from telecommunications legislation in the US, Canada, and elsewhere), it refines and expands these in light of contemporary internet initiatives. It thus presents a list of for public broadband infrastructure – a checklist of principles for building and operating them in the public interest. We examine each of these infrastructural characteristics in turn, describing what is meant by the term, and how it has been used in policy development as well as the relevant scholarly literature. These desiderata are illustrated using case studies of community/municipal wireless initiatives in North America. The paper also discusses how the desiderata can be used as a tool for assessing proposed and operational broadband networks.

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)0.002
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.269
Threshold uncertainty score0.520

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.256
Teacher spread0.237 · 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 designTheoretical or conceptual
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

Citations6
Published2007
Admission routes2
Has abstractyes

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