Bibliographic record
Abstract
Writing Travel in Central Asian History, an eclectic collection that spans from the sixteenth to the twentieth century, offers contributions from historians, literary scholars, and ethnomusicologists. It focuses on outsider views from Great Britain, Germany, Russia, Persia, India, China, and Japan. Central Asia emerges as a “cultural contact zone” (1). The region attracted traders, diplomats, religious figures, and, later, geographers and travel writers. We gain a sense of the evolving goals of outside powers: Russian and Persian missions sought to halt a burgeoning slave trade; Indian princedoms sought allies; Chinese Qing bureaucrats sought to categorize and rule the peoples on the edge of their empire; German anthropologists sought an “Aryan heartland”; and the British worked to define geographic markers to their advantage in the nineteenth century “Great Game” with the tsarist empire. The bounds of Central Asia remain unclear. Apparently this region includes all lands between evolving polities of Persia, Russia, China, and India and spreads southward to some point in Afghanistan. Also, as the authors note, the travel writers barely focused on everyday Asian life among average peoples or the elite. Instead, travel writers’ words reflected the narrow interests outlined by their superiors who sent them on the missions, or their own correlation of Central Asia with their home culture. Missing from the collection are samples of travel writing prevalent in the nineteenth century that presented the region’s peoples as worthy of study, if only for their exoticism.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.010 |
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".