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Record W2160766643 · doi:10.14507/epaa.v22n88.2014

The Use of Online Strategies and Social Media for Research Dissemination in Education

2014· article· en· W2160766643 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEducation Policy Analysis Archives · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsQueen's University
Fundersnot available
KeywordsSocial mediaPublic relationsTerminologyThe InternetInformation DisseminationEmpirical researchDisseminationBest practiceSociologyPolitical scienceWorld Wide WebComputer science

Abstract

fetched live from OpenAlex

Alongside a growing interest in knowledge mobilization (trying to increase the connection between research, policy and practice) there has been a transformation of how knowledge is produced, accessed and disseminated in light of the internet and social media strategies. Few studies have explored the use of social media for research dissemination. This paper explores the online strategies used by 44 research brokering organizations (RBOs) in education across Canada. It is organized in four parts. The first provides a literature review of the terminology associated with Web 2.0 and social media as well as outlines the sparse empirical work that exists. The second presents empirical findings of online practices of 44 RBOs. The third section reports on the frequency of social media activity of RBOs as well as the nature of posts in order to ascertain whether or not research is actually being disseminated through these mechanisms. The final section discusses the implications of social media for research dissemination. Overall, use of additional online strategies by RBOs (other than websites) remains modest. Many of the strategies used are passive and do not allow two-way communication. Thirty percent of RBOs use social media; however, this usage in not pervasive and Facebook and Twitter networks are small. Other mechanisms to encourage active participation will be required alongside Web 2.0 and social media tools, if these strategies are to become robust avenues for knowledge mobilization and research dissemination.

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.

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.443
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
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 head0.124
GPT teacher head0.504
Teacher spread0.380 · 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