The Lure of Cultural Authenticity: Netflix and Speculative Koreanness in the Global Media Market
Bibliographic record
Abstract
Despite Netflix’s status as a dominant global streaming service, it is irrefutable that the platform has facilitated the circulation of media content from different national markets to its subscribers around the world. This increased circulation has been accompanied by the platforms’ exploration of local cultures for global audiences. Specifically, Netflix has sought to represent and repackage local cultures in allegedly “authentic” ways. Drawing on a critical analysis of Netflix’s industry discourses, interviews with Korean content creators, and a textual analysis of the original Korean series Squid Game (2021–present), the article explores how Netflix formulates and disseminates its lore of cultural authenticity as a distinct brand to enhance its international presence. We argue that Netflix’s branding of original Korean series as culturally authentic, further grounded in a particular mode of portraying Korean culture for imagined global (non-Korean) audiences, involves representational practices of what we refer to as speculative Koreanness.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.017 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".