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Record W4285088655 · doi:10.3390/rel13070641

On Bonshakuji as the Penultimate Buddhist Temple to Protect the State in Early Japanese History

2022· article· en· W4285088655 on OpenAlexafffund
George A. Keyworth

Bibliographic record

VenueReligions · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicJapanese History and Culture
Canadian institutionsUniversity of Saskatchewan
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsBuddhismEmperorSanskritChinaAncient historyState (computer science)HistoryHistory of ChinaArtLiteratureArchaeology

Abstract

fetched live from OpenAlex

During the 740s in Japan, the emperor established Buddhist temples in nearly all the provinces, in which three Buddhist scriptures were chanted to avert natural disasters. Tōdaiji, in the recently constructed capital, was the head temple of a network of Temples of Bright Golden Light and Four Heavenly Kings to Protect the State. The principal Buddhist scripture followed in these temples was the Golden Light Sūtra, translated from Sanskrit into Chinese in Tang China at the beginning of the 8th century. This article investigates the history of an understudied example of one of these temples, called Bonshakuji. Emperor Kanmu (r. 781–806) repurposed it in 786 after the introduction from China of novel rituals to protect the state. It had among the most important Buddhist temple libraries, which came to rival perhaps only that of Tōdaiji through the 12th century. I also examine how and why scholar officials and powerful monastics, particularly those associated with the so-called esoteric Tendai and Shingon temples of Enryakuji and Miidera, and Tōji and Daigoji, respectively, utilized the library of Bonshakuji and older and novel state protection texts kept there to preserve early Japanese state-supported Buddhist worldmaking efforts long after that state had become virtually bankrupt.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.609
Threshold uncertainty score0.999

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 studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.027
GPT teacher head0.281
Teacher spread0.254 · 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
Published2022
Admission routes2
Has abstractyes

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