Deserts, Natives, and Sylvan Cities: Russian Turkestan in American Travel Writing, 1890s – 1910s
Bibliographic record
Abstract
The Russian conquest of Turkestan (the territories of modern Turkmenistan, Uzbekistan, Tajikistan, most of Kirghizstan, as well as the southern and southeastern areas of Kazakhstan), completed within three decades from the mid-1860s, brought controversial changes in the region’s economy, administration, and native lifestyle. The gradual emergence of railways and the development of agriculture (primarily cotton growing) attracted American entrepreneurs and travelers. This article covers two travel accounts in book form – parts of Siberia and Central Asia (1899) by Ohio businessman and philanthropist John Bookwalter (1839–1915) and Turkestan: “The Heart of Asia” (1911), written by journalist, travel writer, and diplomat William Curtis (1850–1911). I use the term “imperial view” to argue that the two Americans, despite their different social background and almost a decade passed between their travels, wrote about Russian Turkestan in a similar manner. They hoped to see the transformation of the “empty” nature of Turkestan for economic development, praised new Russian cities compared to native settlements, and created the image of Russia performing a “civilizing” mission in the region while lauding American economic presence there. However, they wrote differently about Central Asia as a geopolitical region due to the different life experiences of the authors and changes in the stance of both Russia and the U.S. in world politics in the 1900s.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.011 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".