Music of the Martial Arts: Rhythm, Movement, and Meaning in a Chinese Canadian Kung Fu Club
Bibliographic record
Abstract
This dissertation is an investigation of the percussion used to accompany Chinese martial arts and lion dancing at Toronto, Canada’s Hong Luck Kung Fu Club. It is based on six years of participant-observation and performance ethnography there, as well as a nine-month period of comparative fieldwork in Hong Kong. The diasporic environment presented questions of identity, and the research also engaged with the emerging field of martial arts studies. The discussion’s primary lines of inquiry are the use of percussion-accompanied lion dance and kung fu in the construction of identity for performers and audiences in a multicultural context; embodied knowledge in the movement and music that undergirds a Chinese, martial way of being-in-the-world; and the experience of learning, performing, and observing these practices. This study draws on phenomenology, semiotics, practice theory, and cognitive semantics, which have been tempered by discipleship at Hong Luck. The primary argument of this dissertation is that, despite the challenges of diaspora, Hong Luck’s transmission process uses intense physical training to engrain a distinctly Chinese, martial habitus onto practitioners; this set of dispositions is the prerequisite for becoming a drummer and is sonically—and physically—manifested in percussion-accompanied kung fu and lion dancing with important implications for the identity of performers and patrons. The main thesis is augmented by an argument for experiencing combat skills through music. With over fifty years of history, the ideals of self-strengthening, resistance to domination, and respect for Chinese culture that are embodied in Hong Luck’s practices have had a lasting impact on not only the local Chinatown community, but also the Greater Toronto Area and beyond.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.016 | 0.010 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".