Bibliographic record
Abstract
While defining martial arts is not prerequisite to philosophizing about them, such a definition is desirable, helping us resolve disputes about the status of hard cases. At one extreme, Martínková and Parry argue that martial arts are distinguished from both close combat (as unsystematic) and combat sports (as competitive), and from warrior arts (as lethal) and martial paths (as spiritual). At the other extreme, mixed martial arts pundits and Bruce Lee speak of combat sports generally as martial arts. I argue that the fine-grained taxonomy proposed by Martínková and Parry can be usefully supplemented by a broader definition, specifically the following: martial arts are systematic fighting styles and practices as ways of embodying wisdom. A possible difficulty here is that such views face the charge of overemphasizing the “philosophical” aspect of martial arts. My definition can, however, avoid this apparent problem. If martial arts essentially aim to embody wisdom, this applies no less to the (strategic) practical wisdom of The Art of War than to the (ethical) practical wisdom of the Tao Te Ching. In an extended sense, then, any systematic fighting style, including combat sports, may count as a martial art insofar as it embodies wisdom by improving practical fighting skills.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.032 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| 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".