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Record W4231733085 · doi:10.32920/ryerson.14639895

Broadband Internet Usage Outside the Home: Insights from a Study of Toronto Internet Cafés

2021· preprint· en· W4231733085 on OpenAlexaffabout
Catherine A. Middleton

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicICT Impact and Policies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsBroadbandThe InternetInternet accessTelecommunicationsBusinessBroadband networksInternet privacyWork (physics)AdvertisingWorld Wide WebComputer scienceEngineering

Abstract

fetched live from OpenAlex

This paper addresses a simple question. In an environment where more and more people have broadband internet access at home, what is the role of internet cafés? In answering this question, a contribution is made to the limited existing knowledge of how consumers use public internet points, with a specific focus on how broadband services are used. This study is novel because work to date has focused on understanding how consumers use broadband in their homes, with the assumption being that once everyone has residential broadband connectivity, public access points like internet cafés will disappear. This paper offers a description of user behaviours observed in 28 internet cafés and 4 free public access points. The paper documents diversity in users and usage patterns, and suggests that internet cafés continue to offer valuable services to their users. Broadband connectivity is used for gaming, but few other uses that required broadband connectivity were observed.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.276
Threshold uncertainty score0.556

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.017
GPT teacher head0.247
Teacher spread0.230 · 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 designObservational
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

Citations3
Published2021
Admission routes2
Has abstractyes

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