Bibliographic record
Abstract
The ancient Chinese theatre system was described in Xian Qing Ou Ji by Li Yu (1611-1680), and can be translated as ‘Speaking honestly, if an actor wants to perform a role, it means that the actor speaks instead of the inside thought, so the actor must put their heart into the role to be real during the performance. Actors need to be in the scene personally and there should be true feeling in it.’ The actor should convey their emotions to the audience and must put their whole heart into the character’s background to show their imagination on the stage; this is also an important theory by Stanislavski. From ancient to contemporary theatre theory, and from Chinese theatre to the European theatre, both imagination and physical techniques are crucial to performance. Kunqu opera’s performance convention and formula also may improve actors’ performance techniques. This research integrated Chinese theatre and Europe theatre practice for further expansion and development. Actors’ skills relate to their imagination and physical movement. This research has enriched existing universal performance training methods, and the significance proves the Kunqu opera training be beneficial to contemporary actor’s physical.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".