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The Roles of Digital Literacy in Social Life of Youth

2018· book-chapter· en· W4255367843 on OpenAlexaff
Dragana Martinović, Viktor Freiman, Chrispina Lekule, Yuqi Yang

Bibliographic record

VenueAdvances in library and information science (ALIS) book series · 2018
Typebook-chapter
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsUniversité de MonctonUniversity of Windsor
Fundersnot available
KeywordsInformation and Communications TechnologyInternet privacyThe InternetDigital literacyPublic relationsLiteracyPerceptionPsychologySocial mediaPolitical sciencePedagogyComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

This chapter contains findings related to social aspects of digital activities of youth. Computers, mobile devices, and the internet are increasingly used in everyday social practices of youth, requiring competencies that are largely still not being taught in schools. To thrive in the digital era, youth need to competently use digital tools and define, access, understand, evaluate, create, and communicate digital information. Being able to develop perceptions of, and respect for, social norms and values for functioning in the digital world, without compromising one's own privacy, safety, or integrity is also important. After addressing the social prospects of information and communication technology (ICT) use among youth, this chapter describes their online behavior through the paradoxical nature of the internet (i.e., providing opportunities for social development vs. introducing risks). Educators and youth services are advised to consider these factors in designing flexible, innovative, and inclusive programs for young people that use ICT.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.982
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.007
Scholarly communication0.0000.478
Open science0.0010.000
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 head0.010
GPT teacher head0.272
Teacher spread0.262 · 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 teacher head, not a consensus.

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

Citations11
Published2018
Admission routes1
Has abstractyes

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