Transcultural fandom of the Korean Wave in Latin America: through the lens of cultural intimacy and affinity space
Bibliographic record
Abstract
This article has examined how the Hallyu phenomenon is integrated into a transnational global cultural landscape, focusing on Chilean reception of K-pop. It analyzed how Hallyu fans engage with a social media-saturated environment in Chile, mapping out transnational pop cultural flows within the digital media environment through which the participatory culture of media users is spread. What is interesting is that Chilean society, in general, shows negative attitudes toward K-pop fans. More importantly, while many Chileans consider K-pop fans weird and strange, often disparaging their family members and friends for liking such music, the marginalization of K-pop fans in Chile promotes a greater sense of bonding among them through the affinity spaces of social media. Under this circumstance, most of our interviewees explained that digital media plays a vital role in the dissemination of K-pop in Chile and Latin America. Unlike Hallyu fans in other regions, K-pop fans in Chile have developed cultural intimacy specific to digital site-media, primarily in the realm of social media, and K-pop generates the creation of affinity spaces via different social media platforms.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".