THE PAMIR EXPEDITIONS OF MIKHAIL IONOV (1891-1895)
Bibliographic record
Abstract
In the last quarter of the 19th century, the Russian government stepped up its activities in Central Asia, organizing a number of research expeditions to explore the Tien Shan and the Pamir Mountains. In connection with the increased activity of the British in this region in the late 1880s - early 1890s, several military topographic expeditions were sent to the Pamirs in 1891-1894. In addition to geodetic reconnaissance, photography of the Pamir landscapes was carried out for the first time. The article considers the second, 1892, Pamir campaign under the command of Colonel Mikhail Efremovich Ionov, aimed at conducting reconnaissance and restoring Russia’s rights in the Pamirs. During the expedition, Ionov organized an administration of the native population of the Pamirs. Russian military researchers of Central Asia were members of the Geographical Society and were part of the Corps of Military Topographers. In the Pamir campaigns, the task of this department was reduced to geodetic reconnaissance and the development of routes for the movement of troops and the establishment of garrisons at border points. The basis of the publication is a series of photographs taken by S. P. Yudin, an artist, photographer and participant in this campaign. His photographs are currently stored in the archives of the Museum of Geography of Moscow State University.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".