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Record W144649894 · doi:10.32920/ryerson.14639082

Understanding the Benefits of Broadband: Insights for a Broadband Enabled Ontario

2021· preprint· en· W144649894 on OpenAlexafffundabout
Catherine A. Middleton

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicICT Impact and Policies
Canadian institutionsToronto Metropolitan University
FundersSocial Sciences and Humanities Research Council of CanadaEconomic Development AdministrationIndustry CanadaEuropean CommissionU.S. Department of Commerce
KeywordsBroadbandEnablingBusinessBroadband networksBeneficiaryTelecommunicationsProductivityIndustrial organizationEconomic growthEconomicsComputer scienceFinance

Abstract

fetched live from OpenAlex

This paper reviews the international literature on broadband network developments and assesses the claims of social and economic benefits attributed to broadband initiatives. The paper reveals a current disconnect between societal level goals for increased citizen participation in the knowledge economy, and individual broadband usage that is centred around communication and entertainment activities. The paper points to the crucial, and often overlooked role that communal level broadband initiatives can play in extending services to citizens, and in improving interactions between governments and their constituents. It is noted that the clearest beneficiary of global broadband deployments is the commercial sector. Although broadband technologies are being widely adopted by consumers, and heavily promoted by governments, it is observed that their impacts to date are subtle, rather than spectacular. It is difficult to identify a set of applications or services that would be essential to a broadband enabled Ontario, but given the perceived importance of broadband as an enabler of competitiveness and productivity, it appears that an agenda to increase broadband capacity and services in Ontario is a reasonable one. The paper concludes by presenting a number of issues to be considered in the development of a strategic vision and agenda for ‘broadband enabling’ the Ontario economy.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.553
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.066
GPT teacher head0.247
Teacher spread0.180 · 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 designSimulation or modeling
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

Citations8
Published2021
Admission routes3
Has abstractyes

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