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Record W4210835741 · doi:10.32920/ryerson.14638464.v1

Should the Internet Be Everywhere? Perspectives on Ubiquitous Internet Access

2021· preprint· en· W4210835741 on OpenAlexafffundabout
Teresa Ritter, Alison Powell, Catherine A. Middleton

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicICT Impact and Policies
Canadian institutionsConcordia UniversityToronto Metropolitan UniversityYork University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsThe InternetInternet applianceInternet privacySociology of the InternetInternet transitWorld Wide WebComputer scienceInternet accessInternet presence managementInternet research

Abstract

fetched live from OpenAlex

The AOIR 5.0 call for papers asks, “Is the internet everywhere?” This paper poses complementary questions: “Should the internet be everywhere?”, and if the internet should be ubiquitous, what should it look like? Drawing from Canadian focus group data, the paper explores experienced internet users’ opinions and attitudes about the value of the internet, demonstrating that despite its widely recognized benefits, many people embrace the internet somewhat reluctantly. The paper identifies four types of internet users who dynamically engage with the technology in different ways. Each type of user bears a set of distinguishing characteristics, which are drawn from analysis of internet users’ discussions about their activities on the internet, and their attitudes toward it. This paper considers how (or whether) ubiquitous internet access could be of benefit to each type of user, concluding that ubiquitous internet access is not yet expected to be in great demand by all types of internet users.

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)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.014
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0050.022
Scholarly communication0.0130.014
Open science0.0010.005
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.056
GPT teacher head0.316
Teacher spread0.259 · 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 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

Citations0
Published2021
Admission routes3
Has abstractyes

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