How Does <i>Jade Dynasty</i> Become a Big IP? Mapping Digital Media Ecology in Contemporary China
Bibliographic record
Abstract
Abstract Jade Dynasty (Zhuxian) emerged as one of the pioneering and most celebrated online novels of the early 2000s in China. First serialized online in mainland China around 2002 and later published as a book series in Taiwan between 2003 and 2007, JD has been expansively adapted across various media forms, including video games (from 2007 to the present), TV dramas (2016), films (2019), and animation series (starting from 2022). Scholars acknowledge it as a pioneer in the transmedia adaptation of Chinese online novels, highlighting its significant IP (intellectual property) impact. In the realm of transmedia storytelling, scholars have pointed out different production modes, including media convergence, media mix, and “affective modules” regulated by digital platforms. Referring to the emphasis on media connections made in the studies of media mix and the issue of intermediality indicated in IP, this paper investigates the digital media ecology manifested in the transmedia system of the Jade Dynasty. By examining the online fantasy novel in the early 2000s, the video game in the mid-2000s, and the animation series in the 2020s, this study argues that each stage represents significant turning points in the contemporary Chinese digital media industry.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".