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Record W4245592334 · doi:10.32920/ryerson.14668122

The transformation of network neutrality in Canada

2021· preprint· en· W4245592334 on OpenAlexaffabout
Natalie Andrusko

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldComputer Science
TopicNetwork Traffic and Congestion Control
Canadian institutionsToronto Metropolitan UniversityMcMaster UniversityYork University
Fundersnot available
KeywordsNet neutralityInternet transitThe InternetComputer scienceNetwork managementInternet accessComputer networkDeep packet inspectionInternet trafficNetwork packetBandwidth managementTelecommunicationsBroadbandComputer securityBandwidth (computing)World Wide Web

Abstract

fetched live from OpenAlex

"Telecommunications technology has dramatically transformed an individual's ability to access information. Internet surfers are often unaware of the ways in which their Internet services are being managed, and even fewer are familiar with the term Internet neutrality. As a growing trend, more Internet Service Providers (ISPs) in Canada are intervening with the infrastructure of the Internet by utilizing traffic management practices, such as bandwidth 'throttling'1, which hinder a user's ability to quickly access certain types of content online. Internet traffic management practices (ITMP) are a means for ISPs to control their 'congested'2 networks, with the aim of optimizing or improving their network's performance, or they can often aid in increasing usable bandwidth (Lithgow, 2011). Traffic management practices ultimately allow one kind of 'packet'3 to be delayed over another; for example, ISPs often use a program called Deep Packet Inspection (DPI), which is a program that can identify forms of traffic online, meaning it can target specific applications. Since ITMPs can target specific 'packets' online, smaller interest groups, and businesses became increasingly concerned that network neutrality policy principles, such as 'common-carriage'4 was not being enforced by the CRTC. This paper will identify the main concerns of utilizing ITMP on broadband networks, and will illustrate that ITMP can and should be connected to the discussion regarding network neutrality in Canada" -- From the introduction, page 1.

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: none
Teacher disagreement score0.907
Threshold uncertainty score0.431

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)0.0000.000

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 head0.010
GPT teacher head0.204
Teacher spread0.194 · 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

Citations0
Published2021
Admission routes2
Has abstractyes

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