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Youth Engagement in the Era of New Media

2016· book-chapter· en· W2550426564 on OpenAlexaff
Yoshitaka Iwasaki

Bibliographic record

VenueAdvances in public policy and administration (APPA) book series · 2016
Typebook-chapter
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPopularitySocial mediaYouth studiesMeaning (existential)Variety (cybernetics)Diversity (politics)SociologyPublic relationsPositive Youth DevelopmentPolitical sciencePsychologySocial psychologyGender studiesComputer science

Abstract

fetched live from OpenAlex

Contextualized within the popularity of new media, youth engagement is a very important concept in the practice of public involvement. Guided by the current literature on youth engagement and media studies, this chapter examines the key engagement-related notions involving youth and media usage. Being informed by a variety of case studies on youth engagement through the use of media within various contexts globally, the chapter discusses the opportunities and challenges of engaging youth through media usage. The specific notions covered in this chapter include: 1) the role of “hybrid” media in youth engagement; 2) “intersectionality” illustrating the diversity of youth populations and their media usage; 3) meaning-making through media usage among youth; and 4) building global social relationships and social and cultural capital through youth's media usage. Importantly, the use of new media can be seen as a means of reclaiming and reshaping the ways in which youth are engaged, as key meaning-making processes, to address personal, social, and cultural issues.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.006
Scholarly communication0.0110.009
Open science0.0010.009
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.002

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 head0.061
GPT teacher head0.343
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 designNot applicable
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

Citations0
Published2016
Admission routes1
Has abstractyes

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