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Record W7034411884

Text and Context: Redemptive Societies in the History of Religions of Modern and Contemporary China

2012· other· en· W7034411884 on OpenAlexaboutno aff

Bibliographic record

VenueQucosa (Saxon State and University Library Dresden) · 2012
Typeother
Languageen
FieldSocial Sciences
TopicChinese history and philosophy
Canadian institutionsnot available
Fundersnot available
KeywordsSubject (documents)ChinaPoliticsFocus (optics)Key (lock)History of China
DOInot available

Abstract

fetched live from OpenAlex

In recent years, scholars of modern and contemporary Chinese religion have turned their attention to the subject of “redemptive societies”, a term coined by Prasenjit Duara in 2001 to refer to groups such as the Yiguandao, the Daoyuan, the Tongshanshe , the Wushanshe, and others which had a major socio-religious impact during the Republican period. Spiritually authoritative or sacred texts play a number of crucial roles within redemptive societies. First and foremost, of course, they record and codify a redemptive society’s beliefs and rituals and are thus key sources for the analysis of these aspects of a specific religious system. As obvious as this may appear, such analyses have not been carried out for many of these texts, which more commonly serve as quarries in which to collect data on the organizational structure or social and political history of a particular group. Research that takes the doctrinal systems encoded in modern redemptive societies’ sacred texts seriously has been fairly rare. We have therefore put together an international team of scholars from Europe, Taiwan, Canada, China, Hong Kong, and Japan to focus on the textual and contextual histories of redemptive societies, with an eye toward giving their past – and their future – the attention they deserve.

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)0.002
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 score0.023
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.006
Science and technology studies0.0050.009
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.024
GPT teacher head0.220
Teacher spread0.196 · 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
Published2012
Admission routes1
Has abstractyes

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