Historiography of the Korean Wave: Cultural Shifts of Genres and Themes in the Screen Industry
Bibliographic record
Abstract
Korean screen culture, including television dramas and film, has rapidly changed in genres and themes over the past several decades. The Korean screen industries have substantially advanced the quality of their local cultural content through diverse strategies; in particular, the diversification of genres and themes. Cultural genres and themes are significant elements because they are some of the most important standards in understanding the primary characteristics of screen culture. What is interesting is that contemporary cultural programs, including Kingdom (2019, 2020), Squid Game (2021), Hell (2021), and All of Us Are Dead (2022), are relatively new as they are zombie genre dramas. In the Korean screen industry, the zombie is a new genre, which is unprecedented. However, the common theme of these programs is not new but is similar to the local dramas and films of the 1970s and the 1980s as they still portray several sociocultural issues, such as people’s struggle and economic divide, running through contemporary Korean society. By utilizing a historical approach in tandem with textual analysis, this paper analyzes the major characteristics of contemporary Korean screen culture in content. It investigates Korean film and dramas in terms of genres and themes so that we understand the cultural transformation of the Korean screen industry. Then, it explores the swift change experienced by the Korean screen industry. Through the historical analysis of the genres and themes of Korean dramas and films, it attempts to shed light on the nature of the shifting patterns of genres and themes in local cultural content.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".