State policy on the network of rural settlements in the second half of the XIX - first quarter of the XX century (by the example of the Tomsk district of the Tomsk province)
Bibliographic record
Abstract
The article analyzes the state policy in the second half of the XIX - first quarter of the XX century in relation to the rural settlement network of the Tomsk neighborhood-district of the Tomsk province. The authors determine that prerequisites for the evolvement of the settlement framework of rural settlements in the territory under consideration began from the moment of the foundation of the first prisons and vigorously continued until the beginning of the XX century. At this stage, a stable pattern of the rural settlement network of the Tomsk neighborhood-district is being formed. The 1900s to the mid-1920s saw an active resettlement process, as a result of which previously undeveloped plots were put into circulation, on which new rural settlements were subsequently founded. The land management process was not curtailed by the Soviet government, but on the contrary, until the mid-1920s it actually continued through the development of territories allocated in pre-revolutionary times. The authors of the article use archival materials found in the archives and libraries of Moscow, Barnaul, Irkutsk and Tomsk. Special attention is paid to the cartographic materials being an appendix to the land-use reports. The materials reflect the dynamics of the land management process of individual groups in volosts of the Tomsk district of the Tomsk province. On the basis of historical maps, which were supported by statistical data for the corresponding period, schematic cartographic models were compiled that reflect changes occurred with the network of rural settlements from the middle of the XIX century to 1925. Via comparison of asynchronical foundations, the authors managed to identify vectors of populating the territory as well as determine stages of land-use management in peasant volosts of the Tomsk district in the early XX century and find out boundaries of resettlement sub-regions of the Tomsk resettlement region.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.005 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.012 | 0.003 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".