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Rinzai Zen Kōan Training

2015· reference-entry· en· W2182689334 on OpenAlexaff
Victor Sōgen Hori

Bibliographic record

Venuenot available
Typereference-entry
Languageen
FieldSocial Sciences
TopicChinese history and philosophy
Canadian institutionsMcGill University
Fundersnot available
KeywordsAutoethnographyPerformative utteranceBuddhismPhilosophyEpistemologyReductionismSociologyTheologySocial science

Abstract

fetched live from OpenAlex

The well-known dictum that Zen is “not founded on words and letters” would seem to make Zen Buddhism inaccessible to philosophy, yet scholars have applied Western philosophical concepts to Zen. Do these philosophical concepts accurately characterize Zen kōan training as it is actually practiced in the Rinzai monastery? Introducing an autoethnography of the author’s own experience in Rinzai kōan practice, this essay provides an account of the moment of “seeing a kōan” and of the considerable literary study required at advanced stages of kōan practice. This autoethnography provides the basis for evaluating some of the philosophical concepts that have been used to characterize Rinzai kōan practice, including J. L. Austin’s notion of a performative speech act and the concept of a pure experience. Finally, Robert Sharf’s charges of phenomenological reductionism are evaluated.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.006
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.002
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.162
GPT teacher head0.347
Teacher spread0.185 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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
Published2015
Admission routes1
Has abstractyes

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