MétaCan
Menu
Back to cohort
Record W6913087483 · doi:10.5683/sp3/2egtbi

Canadian Internet Use Survey, 2018

2020· dataset· en· W6913087483 on OpenAlexaboutno aff

Bibliographic record

VenueBorealis · 2020
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsThe InternetGovernment (linguistics)Digital dividePaceInternet accessDigital governmentOnline participationDigital inclusion

Abstract

fetched live from OpenAlex

The 2018 Canadian Internet Use Survey (CIUS) measures access to the Internet and the online behaviours of individual residents of Canada 15 years of age and over, living in the provinces. The survey is built off the previous iteration of the CIUS, last conducted in 2012. The 2018 iteration has been redesigned and modernized to increase international comparability, answer government policy-relevant questions, and measure a wider range of online activities, given the rapid pace at which the Internet has evolved. The 2018 CIUS aims to measure the impact of digital technologies on the lives of Canadians. Information gathered will help to better understand how individuals use the Internet, including intensity of use, demand for online activities and online interactions. The CIUS examines, use of online government services, use of social networking websites or apps, smartphone use, digital skills, e-commerce, online work, and security, privacy and trust as it relates to the Internet.

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)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation 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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.028
Threshold uncertainty score0.187

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0060.016
Science and technology studies0.0030.000
Scholarly communication0.0030.002
Open science0.0040.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0280.020

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 head0.273
Teacher spread0.217 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations1
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueBorealisFrench-language works237,207