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Christian Communities, Central Asia, 600–1500

2023· other· en· W4361269850 on OpenAlexaff

Bibliographic record

VenueThe Encyclopedia of Ancient History · 2023
Typeother
Languageen
FieldSocial Sciences
TopicEurasian Exchange Networks
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsChristianityAncient historyIslamHistoryBishopsWorshipFifteenthIslamizationGeographyArchaeologyTheologyPolitical sciencePhilosophyLaw

Abstract

fetched live from OpenAlex

Prior to the advent of Islam, Syriac Christianity spread into eastern Khurasan, Bactria, and Sogdiana; Herat, Merv, and Samarkand were all important cities that received metropolitan bishops. Even after the Muslim conquest of Central Asia and subsequent Islamization, Christianity continued to spread among the Sogdians and various Turkic groups, including the Qarluqs and later the Keraits or Onguts. As early as the eighth or ninth century, Christianity was established in the Uyghur Kingdom of Turfan, as testified by manuscript fragments found there. Various sources indicate that there were Christian communities around the Tarim Basin from the tenth to twelfth centuries, with Kashgar the site of a metropolitan bishop. Also in the twelfth century, we hear of Christianity among the Qipchaq Turks. Under the Mongols, Christianity flourished again, thanks to marriage alliances established with the Keraits and Onguts. Besides those who married Mongol rulers, other Christians held positions of influence in the court administration or military and a Turkic monk was even elected patriarch Yahballaha III of the Church of the East. Marco Polo and other sources give valuable information on Christian communities under the Mongols, as do hundreds of gravestones from the time. The end of medieval Christianity in Central Asia seems to coincide with the conversion of Mongol rulers to Islam in the early fourteenth century. By the fifteenth century it had likely all but disappeared, apart from relics of Christian worship, perhaps no longer understood by those who maintained them.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.074
Threshold uncertainty score1.000

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 studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.027
GPT teacher head0.257
Teacher spread0.230 · 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
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
Published2023
Admission routes1
Has abstractyes

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