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Record W2090969900 · doi:10.1080/10584600902854363

Does Internet Use Affect Engagement? A Meta-Analysis of Research

2009· article· en· W2090969900 on OpenAlexaff
Shelley Boulianne

Bibliographic record

VenuePolitical Communication · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsMacEwan UniversityUniversity of Alberta
Fundersnot available
KeywordsThe InternetCivic engagementAffect (linguistics)PoliticsPublic engagementInternet researchMeta-analysisPolitical sciencePsychologyPublic relationsSociologySocial psychologyLawComputer science

Abstract

fetched live from OpenAlex

Scholars disagree about the impact of the Internet on civic and political engagement. Some scholars argue that Internet use will contribute to civic decline, whereas other scholars view the Internet as having a role to play in reinvigorating civic life. This article assesses the hypothesis that Internet use will contribute to declines in civic life. It also assesses whether Internet use has any significant effect on engagement. A meta-analysis approach to current research in this area is used. In total, 38 studies with 166 effects are examined. The meta-data provide strong evidence against the Internet having a negative effect on engagement. However, the meta-data do not establish that Internet use will have a substantial impact on engagement. The effects of Internet use on engagement seem to increase nonmonotonically across time, and the effects are larger when online news is used to measure Internet use, compared to other measures.

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)0.027
metaresearch head score (Gemma)0.071
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.973
Threshold uncertainty score0.141

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.071
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0090.036
Bibliometrics0.0100.011
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.482
GPT teacher head0.541
Teacher spread0.060 · 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.

Study designMeta-analysis
DomainMethods
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

Citations918
Published2009
Admission routes1
Has abstractyes

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