Численный состав и классификация старообрядцев Томской губернии в последней четверти XIX — начале XX в. в контексте государственно-конфессиональной политики Российской империи
Bibliographic record
Abstract
The article is devoted to the study of two main issues in the history of the Old Believers in the Tomsk province — its numerical composition and classification by agreements and sects in the last quarter of the 19th — early 20th centuries. The source base of the work is the materials of the State Archives of the Altai Territory (Barnaul) and the State Archives of the Tomsk Region (Tomsk), as well as some published sources. In the course of the study, various statistical data were analyzed and the reasons for their discrepancies were identified. In addition, the geography of the settlement of Old Believers within the Tomsk province was studied. The process of resettlement of the Old Believers was a consequence of the stateconfessional policy pursued in the Tomsk province and the Russian Empire as a whole. The reasons for the discrepancy between the actual number of Old Believers and the official statistics are established. The author provides a description of the main agreements and sects of the Old Believers. An important conclusion is made that in its content, the Old Believers of the Tomsk province did not differ fundamentally; the agreements and sects here were the same as in Central Russia. This was a consequence of the active forced and voluntary migration process of Old Believers to the territory of Western Siberia, including Tomsk province. In quantitative terms, in the Tomsk province in the last quarter of the 19th — early 20th centuries, representatives of the Starikovshchina, Pomorskoye consent and Popovshchina predominated.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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".