MétaCan
Menu
Back to cohort
Record W6912993786 · doi:10.5683/sp3/i4nxe4

Canadian Internet Use Survey, 2010 [Canada]: Persons file

2010· dataset· en· W6912993786 on OpenAlexaffabout

Bibliographic record

VenueBorealis · 2010
Typedataset
Languageen
Field
Topic
Canadian institutionsStatistics Canada
Fundersnot available
KeywordsThe InternetMetropolitan areaScope (computer science)CensusMeasure (data warehouse)Internet accessSurvey data collectionSurvey methodology

Abstract

fetched live from OpenAlex

For 2010, the Canadian Internet Use Survey (CIUS) was redesigned to better measure the type and speed of household Internet connections. It is a hybrid survey that measures both household Internet access and the individual online behaviors of a selected household member. It replaces the previous CIUS, a biennial survey conducted in 2005, 2007 and 2009. As the new survey has two distinct conponents - household and individual - with revised and streamlined question, it is not appropriate to directly compare results from these two surveys in most cases. The CIUS measures the availability, type, and speed of home Internet connections. It then selects a member from the household to measure the extent and scope of online behavior including the location, frequency and intensity of use, specific uses including the purchase of products and services (electronic commerce), and other related issues such as online security practices. This content is supplemented by individual and household characteristics (e.g., age, income, family type) and some geographical detail (e.g. province and Census Metropolitan Area).

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)0.007
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 score0.035
Threshold uncertainty score0.172

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0080.029
Science and technology studies0.0020.000
Scholarly communication0.0030.001
Open science0.0040.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0350.024

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 head0.028
GPT teacher head0.241
Teacher spread0.213 · 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

Citations0
Published2010
Admission routes2
Has abstractyes

Explore more

Same venueBorealisFrench-language works237,207