MétaCan
Menu
Back to cohort
Record W2327902591 · doi:10.7790/tja.v61i4.273

Canada's telecommunications policy environment

2011· article· en· W2327902591 on OpenAlexaffabout
Catherine A. Middleton

Bibliographic record

VenueTelecommunications Journal of Australia · 2011
Typearticle
Languageen
FieldEngineering
TopicICT Impact and Policies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsTelecommunicationsBusinessComputer science

Abstract

fetched live from OpenAlex

This paper provides an overview of the telecommunications policy environment in Canada. Like Milner's (2009) article on New Zealand, this paper offers insights on international approaches to telecommunications policy. Canada's telecommunications history reveals a mix of private and public sector investment in regionally-based service providers. Canada did not have a single, publicly owned telecommunications carrier as was the case in Australia. Liberalisation of the telecommunications marketplace encouraged the development of competing infrastructures, with cable companies (traditionally focused on broadcasting distribution) and telephone companies now both providing wireline and wireless, voice, Internet and television services. Competition for wireline services remains regionally based, while wireless providers compete nationally. Although competition is intense, the broadband and wireless markets are highly concentrated. Competition in these markets has not resulted in extensive consumer choice, low prices or innovative services. Most Canadian consumers have access to broadband connectivity, but uptake rates now lag other OECD countries, for services that are slower and more expensive than those available in many other locations. Mobile phone penetration in Canada is on par with that of developing nations. The paper explores the characteristics of Canada's telecommunication markets, discusses the policy environment and notes that government has not offered a vision of a digital future for Canada.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.260
Threshold uncertainty score0.961

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.054
GPT teacher head0.276
Teacher spread0.222 · 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 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

Citations13
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueTelecommunications Journal of AustraliaSame topicICT Impact and PoliciesFrench-language works237,207