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International conferences dedicated to the history of the Chinggisid states

2024· article· en· W4403227046 on OpenAlexaboutno aff
Talapker A. Ualiyev

Bibliographic record

VenueGolden Horde Review · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicLinguistics and Cultural Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHistory

Abstract

fetched live from OpenAlex

On August 19, 2024, Astana hosted an international conference on “Topical issues on the history of the Kazakh Khanate from the second half of the 15th – first half of the 18th century”. On August 20–21, another international conference was held, entitled, “Ethnopolitical history of the Jochi, Chagatai, Haidu and Moghulistan uluses” and dedicated to the 800th anniversary of the formation of the Jochid Ulus. The event was organized by the Ministry of Science and Higher Education of the Republic of Kazakhstan, the Scientific Institute for the Study of the Jochid Ulus. More than 70 leading scientists, specialists and researchers researching the history of nomadic societies and empires, including the history of the Kazakh Khanate and the Golden Horde, from Kazakhstan, Russia, Uzbekistan, China, Canada, Japan, and Austria participated in the conferences. The conferences discussed the issues of studying the Kazakh Khanate and the ethnopolitical history of the Jochi, Chagatai, and Haidu Uluses which were formed during the collapse of the Mongolian Empire. Moreover the participants discussed the issues of developing the fourth volume of the History of Kazakhstan and creating a separate book dedicated to the history of the Kazakh Khanate. Within the framework of the 2nd conference dedicated to the history of the Jochi, Chagatai, Haidu uluses, and Moghulistan, a private screening was organized for the documentary film “Batu: Historical Detective” created by Kazakh director Rashid Nugmanov. The was contributed to by historians and researchers from Kazakhstan, Russia, Ukraine, Mongolia, France, Canada and the USA.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.486
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.064
GPT teacher head0.276
Teacher spread0.212 · 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
GenreReview

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
Published2024
Admission routes1
Has abstractyes

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