“Frogs don’t remember when they were tadpoles”: searching for love in South Korea’s “cyber gay ghetto”
Bibliographic record
Abstract
This paper examines the contradictory role of the Internet in shaping the cisgender gay male community in the non-liberal and communitarian context of South Korea. Despite its global status as a cultural powerhouse with one of the world’s most networked economies, Korea is notorious for its strict regulation of gender roles and sexual conduct. Since the mid-1990s, its gay population has utilized the BBS (Bulletin Board Service) and the Internet to evade familial surveillance and forge discreet gay lifestyles. Nonetheless, challenging the liberatory discourse of the Internet associated with the worldwide phenomenon of “queer globalization,” this technology is now contributing to the mutual estrangement of gay men from each other and the broader Korean society. Not only do they have to jump through the hoops of each other’s reified sexual preferences to connect with the community organized as a neoliberal market, they have to contend with the pressures of conforming to a hetero-masculinist culture based in the overlapping structures of family, work, and military that remain hegemonic in South Korea. Unable to suture this gap between a Korean family-based reality and a white Euro-American gay lifestyle promoted on the Internet, many gay men become stranded as “small tribes within a cyber ghetto.”
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.011 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".