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Record W2486964866

L’apprentissage du shakuhachi japonais et le shugyō, la discipline du soi

2015· article· fr· W2486964866 on OpenAlexvenueno aff
Bruno Deschênes

Bibliographic record

VenueMUSICultures · 2015
Typearticle
Languagefr
FieldArts and Humanities
TopicPhilosophical and Theoretical Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsBuddhismAsceticismCeremonyEnlightenmentThe artsTaoismMartial artsAristocracy (class)Order (exchange)AestheticsArtHumanitiesSociologyVisual artsPhilosophyTheologyLawPoliticsPolitical science
DOInot available

Abstract

fetched live from OpenAlex

Buddhism arrived in Japan from China towards the sixth century. This religion became the aristocracy’s spiritual practice and, later on, that of the samurai class, especially Zen Buddhism. Over the following centuries, Zen Buddhism, significantly tinged with Taoism, had an indelible influence on all Japanese arts, including combat arts and the tea ceremony. The ascetic discipline of Buddhist monks is known as shugyō, a term usually translated as “training,” “apprenticeship,” or “discipline,” but which can also be translated as “self-cultivation.” Shugyō considers that all learning begins with the body in order to attain a state of enlightenment in which the body and the spirit are one, that is to say a body-spirit. According to this concept, in the arts, it is not talent that defines the artist, but the individual self that is deployed across the art. The goal of shugyō is therefore not the acquisition of theoretical knowledge, but rather it concerns spiritual development and the artist’s body-spirit ethic in the face of his or her art.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
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 studies0.0030.004
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.028
GPT teacher head0.236
Teacher spread0.208 · 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
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
Published2015
Admission routes1
Has abstractyes

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