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Record W3007617069 · doi:10.1556/062.2020.00001

PROGNOSTICATION IN CHINESE BUDDHIST HISTORICAL TEXTS THE GĀOSĒNG ZHUÀN AND THE XÙ GĀOSĒNG ZHUÀN

2020· article· en· W3007617069 on OpenAlexfundno aff
Gang Yang, Christoph Anderl

Bibliographic record

VenueActa Orientalia · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicChinese history and philosophy
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of British ColumbiaChina Scholarship Council
KeywordsBuddhismGautama BuddhaParallelsContext (archaeology)AmbiguityNarrativeLiteraturePhilosophyEpistemologyHistoryLinguisticsArtTheology

Abstract

fetched live from OpenAlex

This paper explores topics and techniques of prognostication as recorded in medieval Buddhist historical literature, with an emphasis on the Gāosēng zhuàn 高僧傳 (GSZ) and Xù gāosēng zhuàn 續高僧傳 (XGSZ). The paper first provides a short survey of how prognostication is treated in Chinese Buddhist translated texts. In these ‘canonical’ sources there is clear ambiguity over the use of supernatural powers: on the one hand, such practices are criticised as non-Buddhist or even heterodox; on the other, narratives on Śākyamuni’s former and present lives as well as accounts of other buddhas, bodhisattvas, and the Buddha’s disciples abound with descriptions of their special abilities, including knowledge of the future. In contrast, the GSZ and XGSZ display a clear standpoint concerning mantic practices and include them as integral aspects of monastics’ lives. The two texts articulate that the ability to predict the future and other supernatural powers are natural by-products of spiritual progress in the Buddhist context. This paper discusses the incorporation of various aspects of the Indian and Chinese traditions in monastics’ biographies, and investigates the inclusion of revelations of future events (for example, in dreams) and mantic techniques in these texts. In addition, it traces parallels to developments in non-Buddhist literature and outlines some significant differences between the GSZ and the XGSZ.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.849
Threshold uncertainty score0.702

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.020
GPT teacher head0.270
Teacher spread0.250 · 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.

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

Citations3
Published2020
Admission routes1
Has abstractyes

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