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Record W4224242046 · doi:10.1080/19392397.2022.2063974

BTS for BLM: K-pop, Race, and Transcultural Fandom

2022· article· en· W4224242046 on OpenAlexaff
Michelle Cho

Bibliographic record

VenueCelebrity Studies · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Culture and Media Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFandomNarrativeEthnic groupMedia studiesSocial mediaPoliticsSociologyRace (biology)Gender studiesPolitical scienceArtAnthropologyLawLiterature

Abstract

fetched live from OpenAlex

This cultural report contextualizes K-pop group BTS’s history of engagement with Black pop cultural forms, to aid in assessing the significance of the group’s support for BLM organizations and anti-racist activism following the murder of George Floyd in the summer of 2020. While providing a counter-narrative to that of inter-ethnic antagonism that has been a feature of media discourse on Black-Korean relations in the US, since the 1980s, the report also provides an overview of the online organizing and protest strategies of BTS fans in the BLM movement, and the subsequent discourse about K-pop’s politicization that emerged in media coverage and on social media platforms; By bringing these accounts together, the essay aims to enrich our understanding of the political significance of emergent fan identities, while emphasizing the need for historical grounding in our discussions of race and transnational pop cultural phenomena.

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)0.003
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0130.008
Scholarly communication0.0060.003
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.059
GPT teacher head0.367
Teacher spread0.308 · 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

Citations30
Published2022
Admission routes1
Has abstractyes

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