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Record W2895984242 · doi:10.32920/14636136.v1

The State of Social Media in Canada 2017

2021· article· en· W2895984242 on OpenAlexafffundabout
Anatoliy Gruzd, Jenna Jacobson, Elizabeth Dubois

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsUniversity of OttawaToronto Metropolitan University
FundersCanada Research Chairs
KeywordsSocial mediaConverseSnapshot (computer storage)Political sciencePublic relationsAdvertisingBusinessComputer science

Abstract

fetched live from OpenAlex

Today, billions of people around the world are turning to social media to socialize, conduct business, keep up with the news, as well as discover, discuss, and share information. The significance of this global adoption of a relatively new communication and information technology cannot be overlooked. As a country, Canada has one of the most connected populations in the world. For many Canadians, social media is now a part of their daily routine. Our survey results show that an overwhelming majority of online Canadian adults (94%) have an account on at least one social media platform. This makes it critical for policy makers, researchers, and others to have a better grasp of what social media platforms Canadians are using to connect and converse with one another. This report provides a snapshot of the social media usage trends and patterns amongst online Canadian adults based on an online survey of 1,500 participants (see Methods on p. 16 for more details).

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)0.003
metaresearch head score (Gemma)0.009
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: none
Teacher disagreement score0.152
Threshold uncertainty score0.984

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0070.014
Science and technology studies0.0150.005
Scholarly communication0.0140.003
Open science0.0020.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0130.001

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 head0.031
GPT teacher head0.313
Teacher spread0.282 · 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

Citations24
Published2021
Admission routes3
Has abstractyes

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