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Record W2811118645 · doi:10.1093/jaarel/lfy005

Buddhism and Medicine: An Anthology of Premodern Sources. Edited by C. Pierce Salguero

2018· article· en· W2811118645 on OpenAlexaff
James A. Benn

Bibliographic record

VenueJournal of the American Academy of Religion · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicHistory of Science and Medicine
Canadian institutionsMcMaster University
Fundersnot available
KeywordsBuddhismNothingReading (process)Scope (computer science)Value (mathematics)ClassicsHistoryEpistemologyPhilosophyComputer scienceLinguistics

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.230
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.007
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.022
GPT teacher head0.293
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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