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Record W4387187716 · doi:10.1080/22041451.2023.2249776

Platformization of the Korean Wave: a critical perspective

2023· article· en· W4387187716 on OpenAlexaff
Dal Yong Jin, Kyong Yoon, Benjamin Han

Bibliographic record

VenueCommunication Research and Practice · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Culture and Media Studies
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British ColumbiaSimon Fraser University
FundersAcademy of Korean Studies
KeywordsKorean WaveAudience measurementMedia industryConsumption (sociology)AdvertisingFavouritePoliticsProduction (economics)Korean studiesPolitical sciencePopular culturePhenomenonEconomyMedia studiesBusinessSociologySocial scienceEconomicsPublic relationsLaw

Abstract

fetched live from OpenAlex

By employing the platformization of cultural production from a critical political economy approach, this article analyzes the transition of the Korean cultural industries to the platform-driven phase of Hallyu. By discussing the highly transnationalized and platformized Korean Wave in the shifting global media environment, it examines how Netflix platformizes and appropriates the Korean broadcasting industry through various strategies, such as investing in original content creation, licensing Korean content, and subcontractualization of Korean production. These strategies reveal that Korean cultural industry firms have become subordinated to, and rely on, global OTT platforms. In light of the growing influences of Netflix and other global platforms, the article explores the implications of the platformization of cultural production for the transnational cultural flows of Hallyu.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.016
Scholarly communication0.0090.012
Open science0.0010.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.319
GPT teacher head0.557
Teacher spread0.238 · 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

Citations9
Published2023
Admission routes1
Has abstractyes

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