Berg Encyclopedia of World Dress and Fashion
Bibliographic record
Abstract
East Asia covers an area that is home to a quarter of the world’s population. This volume provides a comprehensive overview of the region, followed by separate sections on China, Korea, and Japan. The section on China covers the Han people, China’s ethnic majority, as well as most of China’s fifty-five minority groups. Festive dress, China’s reputation for distinctive hairstyling, and a wide range of adornments linked to ancient beliefs and traditions are all covered. Overviews of Tibet, Mongolia, and Taiwan are included as well. Traditional and modern aspects of Korean dress are explored in depth, and the importance of the textile and garment industries is highlighted. Street and youth fashion, the history of the kimono, dress and masks for Noh and Kabuki performances, and the work of textile artists who are masters of traditional craft are all covered in the section on Japan. Historical backgrounds and accounts of ancient archaeological evidence are also provided. Accompanied by photographs supplying stunning pictorial evidence, East Asia offers a compelling overview of a land where age-old tradition coexists with bustling, technologically advanced modern states.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.279 | 0.210 |
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".