Wabi-sabi Style: the Collision of the East and West, the Combination of the Fashion and the Nature
Bibliographic record
Abstract
In the past fifty years, Japanese fashion as one of the most prosperous Asian fashions has become a legend in the world fashion field through its special oriental design that breaks the fashion aesthetics with the West as the mainstream in the past. In recent years, wabi-sabi style has become a new fashion trend. As sustainable fashion is advocated by more and more people, the ecological concept wabi-sabi aesthetic holds also accords with the eco-fashion tendency. This paper aims to study the wabi-sabi style in the fashion field, which includes its power to collide with the fashion world dominated by the West, and its ecological function. First of all, this paper compares the aesthetic, religious, and women's fashion history of the wabi-sabi style and the western style. Then, it investigates the fashion collision between the East and the West in terms of design concepts and analyzes the inspiration for the wabi-sabi fashion style. What is more, this paper also integrates the wabi-sabi style and eco-fashion to analyze its positive impact on the environment. Ultimately, this study suggests that although the wabi-sabi style has a minimal influence in the fashion field, it will have a promising future for its sustainability and the comfort it renders to the secular life. The result helps to promote the wabi-sabi style, making more people know about this style and think deeply about their attitude to their lives, and grabbing more attention to wabi-sabi fashion for its environmentally friendly function.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".