THE DEVELOPMENT OF THE CITIES OF THE TOBOLSK PROVINCE IN THE LAST QUARTER OF THE XVIII – EARLY XX CENTURIES (HISTORIOGRAPHY OF THE PROBLEM)
Bibliographic record
Abstract
The study reviews scientific literature concerning the cities of the Tobolsk province in the late XVIII – early XX centuries. The article features the works of scientists, published in the pre-revolutionary period and affecting different sides of the subject in question. The results of the research indicate that before 1917 the scientific works were mainly concentrated on such aspects of urban life as demography, trade, administration, urban space, education, local government, and periodicals. The authors did not distinguish the concept of «social life» as a separate phenomenon, limiting the study of its individual components. The methodology includes the use of techniques and tools of local, systemic, comparative- historical, and problem-chronological methods, as well as developments «history of everyday life» and «new Imperial history». In general, the article emphasizes the expansion of scientific knowledge about the social history of Siberian cities in the post- reform and late Imperial periods, reveals the influence of the researchers ' views on the integration of urban life. The scope of the study is not limited to the interest of historians, urbanists and local historians to the subject of study. Historiographical analysis is relevant from the point of view of modern discussions about the prospects of urban studies, and can also be used in the preparation of textbooks and summaries on Siberian history.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".