Russian Expeditions to the Turkmen Coast of the Caspian Sea in the First Quarter of the 19th Century
Bibliographic record
Abstract
In this article, based on the analysis of Russian literature, memoirs of participants and published materials, documents from the archives of the Russian Federation, the author reconstructed the history of expeditions organized by the Russian authorities to the eastern (Turkmen) shore of the Caspian Sea in the first quarter of the 19th century. The purpose of the expeditions was to find and organize a place for the foundation of the Russian commercial and naval fortifications. Military, officials, scientists, merchants were involved in the expeditions, which were of an intelligence and economic nature. The program of the expeditions was formulated by representatives of the highest authorities of the Russian Empire, the treasury also paid for all the costs of their organization and implementation. The expeditions were equipped and sent to the Turkmen coast from the Astrakhan port, the main Russian point on the Volga-Caspian route. During the expeditions, extremely important scientific data were obtained: on ethnography, socio-economic and cultural life of Turkmen tribes and cartography. It was possible to enlist the support of the heads of the Turkmen coastal tribes, to form a list of goods that was interesting for the local population. The results of the expeditions eventually allowed the Russian authorities to decide on a place to establish their trading post (and port) and begin building the Novo-Petrovsky fortification on Mangyshlak in the 1840s.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".