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Record W2294464289 · doi:10.3233/978-1-61499-415-2-407

Access to Internet in Rural and Remote Canada

2014· article· en· W2294464289 on OpenAlexaffabout
Leanne M. Currie, Charlene Ronquillo, Tania Dick

Bibliographic record

VenueStudies in health technology and informatics · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsNuu Chah Nulth Tribal CouncilUniversity of British Columbia
Fundersnot available
KeywordsThe InternetInternet accessContext (archaeology)GeographyLiteracyPopulationRural areaDigital divideBroadbandRural populationSocioeconomicsEconomic growthTelecommunicationsPolitical scienceSociologyWorld Wide WebComputer scienceDemography

Abstract

fetched live from OpenAlex

Canada is the second largest landmass country in the world, but has one of the lowest population densities. As of 2011, approximately 19% of the Canadian population lives in rural, or remote communities. The purpose of this study was to examine differences in rural and urban access to the Internet and device use in Canada, and to explore differences in access to broadband between Aboriginal and non-Aboriginal communities in Canada. In general rural-dwellers had lower levels of Internet access and despite efforts to increase access to high speed Internet, Aboriginal communities in some regions have limited access. Future research should explore computer and health literacy in the context of rural and remote communities in 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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.595
Threshold uncertainty score0.526

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.056
GPT teacher head0.437
Teacher spread0.381 · 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

Citations5
Published2014
Admission routes2
Has abstractyes

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