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Abuse of the Social Media Brain

2015· book-chapter· en· W2500467128 on OpenAlexaff
Fritz Kohle, Sony Jalarajan Raj

Bibliographic record

VenueAdvances in social networking and online communities book series · 2015
Typebook-chapter
Languageen
FieldArts and Humanities
TopicMedia Influence and Health
Canadian institutionsMacEwan University
Fundersnot available
KeywordsMainstreamSocial mediaPerspective (graphical)CriticismCognitionPsychologySocial cognitive theoryDigital mediaSociologyMedia studiesPublic relationsSocial psychologyPolitical scienceArtVisual arts

Abstract

fetched live from OpenAlex

Despite the criticism in the mainstream press regarding the use and abuse of digital and social media, its use has been increasingly encouraged and supported in schools and universities. This chapter examines the social media behaviour of techy-savvy undergraduate students at NHTV, University of Applied Sciences, Breda, The Netherlands, from the perspective of an independent documentary producer and educator, to determine whether any correlation between the amount of time spent online and the use of cognitive functions exists. Media producers require an audience capable of critical thought, and teachers educate future audiences to acquire the necessary cognitive skills. Hence, the chapter analyses how the viewer's cognitive functions impaired by the use of social and digital media affects the reception of media products. This further leads to a more critical concern about the educators' response to the challenges provided by social and digital media.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.016
Scholarly communication0.0070.006
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.094
GPT teacher head0.317
Teacher spread0.223 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2015
Admission routes1
Has abstractyes

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