Caravan trade of Central Asian merchants with Russia in the first quarter of the 19th century
Bibliographic record
Abstract
The article analyzes the everyday business activity of Asian entrepreneurs who participated in caravan trade with the Russian Empire through the cities of Orenburg region in the first quarter of the 19th century. The specifics of foreign trade operations of merchants from Bukhara, Khiva and Kokand during this period were almost completely ignored by Russian historians in the pre-revolutionary, Soviet and modern periods. The source base of this article consists of unpublished archival documents that shed light on the details of the business activities of merchants from Asia. Letters to the regional and Imperial administration made by Asian entrepreneurs, as well as personal letters from foreign merchants are particularly valuable in this regard. Traders had to deal with a long list of tasks. Before the caravan could go along the required route, it was necessary to hire responsible guides, which was not always possible (guides often turned out to be unreliable, which led to additional expenses for the cargo owners), acquire pack animals, take care of security and prepare a considerable amount of money for various road tolls for travelling through the Kazakh steppe. The merchants who were successful in the caravan trade were characterized by moral and psychological stability, the ability to restrain themselves, not succumbing to momentary desires, and even the skills of using cold weapons and firearms. To resolve issues that were exclusively within the competence of representatives of the Russian regional or central administration, Asian merchants had to possess certain communication skills.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.002 | 0.000 |
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.
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".