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The China-Russia Trade through Nerchinsk and Kiakhta

2024· reference-entry· en· W4399748684 on OpenAlexaff
Ilya Vinkovetsky

Bibliographic record

VenueOxford Research Encyclopedia of Asian History · 2024
Typereference-entry
Languageen
FieldSocial Sciences
TopicInternational Relations and Foreign Policy
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsChinaInternational tradeBusinessGeographyArchaeology

Abstract

fetched live from OpenAlex

Abstract Direct bilateral trade between the Romanov and the Qing Empires began officially with the signing of the Nerchinsk treaty in 1689. State-sponsored caravans initiated in European Russia traveled the lengthy continental route from European Russia across Siberia and the Gobi, arriving in Beijing to conduct trade. But by the second quarter of the 18th century, caravan trade was disrupted by a new arrangement, initiated by the Qing, that in the long term proved more agreeable to both empires: the two sides agreed to demarcate their common border, enforce and patrol it more effectively, and establish a new trading post on the Mongol/Transbaikal frontier. Caravan trade was subsequently phased out, replaced by the more efficient trade at the border hub of Kiakhta, where virtually all of the China-Russia trade was conducted almost exclusively by barter. Strict barter regulations, which became a distinguishing characteristic of the “Kiakhta system,” remained in place into the 1850s. Trade at Kiakhta expanded in the 18th century, and in the 19th century, when growing volumes of tea replaced silk, rhubarb, tobacco, and luxury goods as the chief Chinese export, it boomed. In the early years of China-Russia trade, the Russians offered furs almost to the exclusion of any other exports. But as the populations of the fur-bearing animals plummeted, they diversified their offerings. Textiles and light manufacturing came to play an increasingly important role in the 19th century. The result was that Kiakhta trade stimulated manufacturing in Russia and tea-growing agricultural economy in China. Affecting fashions, tastes, and customs, the exchange of commodities (furs, tea, rhubarb, tobacco, cloth, etc.) led to important changes in Russian and Chinese societies and economies. Ongoing trade between the Qing and the Romanov empire-states, conducted on the Buryat/Mongol frontier, also supported colonization and development, stimulated imperial expansion, and had far-ranging ramifications for the indigenous peoples of the Transbaikal region, Mongolia, Siberia, and Central Asia. Geopolitical changes of the late 1850s, culminating in the 1860 treaties that overturned the rules of China-Russia trade, put an end to Kiakhta’s status as a funnel of transregional and global trade.

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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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.483
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.055
GPT teacher head0.372
Teacher spread0.318 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2024
Admission routes1
Has abstractyes

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