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Record W2332670906 · doi:10.1177/1354856514560316

Reimagining smartphones in a local mediascape

2014· article· en· W2332670906 on OpenAlexaff
Dal Yong Jin, Kyong Yoon

Bibliographic record

VenueConvergence The International Journal of Research into New Media Technologies · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Culture and Media Studies
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British ColumbiaSimon Fraser University
Fundersnot available
KeywordsContext (archaeology)Digital mediaSmartphone applicationAdvertisingSociologySocial mediaLocal communityCommunity engagementMedia studiesMultimediaInternet privacyGeographyComputer sciencePublic relationsPolitical scienceWorld Wide WebBusiness

Abstract

fetched live from OpenAlex

Drawing upon in-depth interviews with young smartphone users, as well as socioeconomic analyses, this study examines a localized media landscape emerging with the smartphone and its applications (apps). With particular reference to young Koreans’ engagement with the popular local app platform, KakaoTalk, the study explores how smartphone technology is reimagined in a local context. The KakaoTalk-scape shows that smartphones and their apps are articulated with community-based local modes of communication and the rhythm of urban space. It also demonstrates that media convergence occurs not only between different media platforms but also between global and local media practices.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.004
Scholarly communication0.0060.007
Open science0.0010.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.075
GPT teacher head0.412
Teacher spread0.337 · 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 designQualitative
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

Citations22
Published2014
Admission routes1
Has abstractyes

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