Buddhism and Medicine: An Anthology of Premodern Sources. Edited by C. Pierce Salguero
Bibliographic record
Abstract
Buddhism and Medicine: An Anthology of Premodern Sources is a remarkable collection of translations of important primary sources related to the theory and practice of medicine and healing from across Buddhist Asia. There is nothing like it in English or any other modern language. Everyone who teaches Buddhism or Asian religions will need to acquire it and will find it of immediate value in their teaching and their deeper understanding of the Buddhist tradition and its many (sometimes unexpected) contributions to the cultures and societies of Asia. I hope that historians of European medicine will also incorporate this volume into their teaching and graduate training, since it offers an excellent introduction to a rapidly growing field of study. The volume is impressive not only because of its size (over 700 pages) and comprehensive scope, but also for the care with which it has been compiled. The individual chapters, written by an impressive array of both established and emerging scholars, are strong, but the editor, Pierce Salguero, has also given a great deal of thought to how such a complex volume might work as a single, integrated study. He is to be congratulated for having given us an essential and much-needed work. I know that I will be re-reading and referring to this volume for many years to come.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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".