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Record W4391138165 · doi:10.1177/13678779231224474

Exploring cultural hybridity, questioning cultural appropriation: Peruvian fans’ responses to Latin tropes in K-pop

2024· article· en· W4391138165 on OpenAlexaff
Kyong Yoon, Camila Alexandra Labarta Garcia

Bibliographic record

VenueInternational Journal of Cultural Studies · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Culture and Media Studies
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsHybridityAppropriationLatin AmericansCultural appropriationSociologyGender studiesAnthropologyHumanitiesPolitical scienceArtPhilosophyLinguisticsLaw

Abstract

fetched live from OpenAlex

Drawing on qualitative interviews with K-pop fans in Lima, Peru, this study explores how Latin fans think about and negotiate K-pop industries’ citations of Latin pop music tropes. It addresses the ways in which K-pop's practices of citing other cultures are perceived by the audience whose culture is cited. The Peruvian fans in this study suggest that the citations of other cultures observed in K-pop offer versatile entry points for them to easily engage in the cultural genre. For them, K-pop is a novel cultural genre that has become an alternative yet intimate cultural resource, especially compared to hegemonic American pop music. By providing an analysis of Latin K-pop fans’ lived experiences through the lens of cultural hybridity and appropriation, this audience study contributes to the field of transcultural media research.

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)0.008
metaresearch head score (Gemma)0.013
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 score0.008
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0080.011
Scholarly communication0.0070.004
Open science0.0010.007
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.264
GPT teacher head0.443
Teacher spread0.179 · 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
Published2024
Admission routes1
Has abstractyes

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