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Record W2907946398

"Dae-Han-Min-Guk": The "Red Devils," Korean Identity, and the 2002 FIFA World Cup

2012· article· en· W2907946398 on OpenAlexaboutno aff
Liv Yoon, Samantha King

Bibliographic record

VenueAsian Journal of Exercise and Sports Science · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Culture and Media Studies
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)DiasporaFootballIdentity (music)Meaning (existential)HistoryMedia studiesCatharsisGender studiesColonialismNational identityPolitical scienceSociologyPsychologyArtLiteratureLawAestheticsPolitics
DOInot available

Abstract

fetched live from OpenAlex

During the 2002 FIFA World Cup, staged in South Korea and Japan, the Red Devils, the supporters of the South Korean football team, made headlines around the world. Taking to the streets in huge numbers—most estimates suggest 7 million people took part in the celebrations over the course of the tournament—they displayed fervor and a sense of unity that commentators found unprecedented. This phenomenon went beyond the physical borders of Korea, moreover, as diasporic Korean communities from Toronto to London celebrated in a similar fashion. Taking seriously the claims of diaspora studies, which seek to understand the relationship of national (and other) identities in transnational context, this study investigates the experiences of Korean and Korean Canadian participants in the Red Devils cheering. Two Koreans and two Korean Canadians participated in semistructured, open-ended interviews designed to understand the meaning of their participation in these events. The major themes that emerged from the interviews include the importance of understanding the cheering in the context of Korea’s colonial history, the importance of a sense of belonging and the traditional “we” culture, and the need for catharsis after economically challenging times.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.478
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.004
Scholarly communication0.0000.002
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 head0.020
GPT teacher head0.297
Teacher spread0.277 · 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; both teacher heads agree on what is shown here.

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

Citations3
Published2012
Admission routes1
Has abstractyes

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