The Asian Conference on Cultural Studies 2023: Official Conference Proceedings
Bibliographic record
Abstract
Aesthetics and the sense of beauty in Japan occupy a special place and are at the foundation of the Japanese national identity.In Japanese culture, every aspect of daily life can become an aesthetic experience.Objects and rituals have to be both beautiful and functional at the same time.This duet of beauty and functionality is illuminated by the constellation of a number of aesthetic concepts.Concept of MA which is often translated as "space between," "mindful pause," or as a "negative space" could also be understood as "active silence" or "presence of absence."From architecture to literature, painting, calligraphy and culinary arts, MA is everpresent in performing arts, martial arts, and all "meditation in motion" practices.Japanese character for MA is part of such words as world, humankind, space, time, moment, circle of friends and many others.This paper will focus on MA in Chanoyu, commonly known as the Japanese tea ceremony, in particular, its applications to the contemplative pedagogy, the ways of teaching and learning of this discipline.The research is based on my students' diaries, which is one of the components of the "Japanese Aesthetics" course taught in a Canadian university.Though Japanese aesthetic concepts are deeply rooted in the country's cultural fabric, it doesn't mean that they cannot appeal to the tastes of non-Japanese.Moreover, I argue that they can be successfully applied as a methodology in various disciplines, pedagogy in particular.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.357 | 0.119 |
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".