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Buddhist Culture in Early Modern Japan

2019· reference-entry· en· W2981499640 on OpenAlexaff
Nam‐lin Hur

Bibliographic record

VenueOxford Research Encyclopedia of Asian History · 2019
Typereference-entry
Languageen
FieldSocial Sciences
TopicJapanese History and Culture
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBuddhismPrayerHistorySubject (documents)Religious studiesNorm (philosophy)Ancient historyPhilosophyPolitical scienceLawArchaeology

Abstract

fetched live from OpenAlex

Abstract Buddhist culture was most active and prosperous in early modern Japan (1600–1868). Buddhist temples were ubiquitous throughout the country, and no one was untouched by Buddhism. Buddhist priests wielded considerable power over the populace, and Shinto was largely subject to Buddhist control. Buddhist culture attained this considerable influence in early modern Japan through the performance of death-related rituals and prayer. Death-related rituals (also known as funerary Buddhism) were rooted in the nationwide anti-Christian policy of the Tokugawa bakufu that utilized the administrative machinery of Buddhist temples. Using the opportunity provided by the anti-Christian policy, Buddhist temples were able to bind all households to death-related rituals and this, in turn, gave rise to the danka system in which dying a Buddhist soon became the norm in early modern Japan. Given the rigid social status, mutual surveillance, and highly regulated nature of everyday life in Tokugawa Japan, people through prayer often turned to Buddhist deities to seek divine help for their wishes or ad hoc solutions to worldly problems. Beyond being sites of prayer services, Buddhist temples also served as spaces of learning, relief, and/or leisure, thus catering to people from all walks of life. Both prayer and play were also integral to Buddhist culture in early modern Japanese society.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.217
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0020.004
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 head0.047
GPT teacher head0.322
Teacher spread0.276 · 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; both teacher heads agree on what is shown here.

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
Published2019
Admission routes1
Has abstractyes

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