Development of Education in Siberia in First Quarter of 18th Century
Bibliographic record
Abstract
The article is devoted to the study of the schooling formation on the territory of the Siberian province in the first quarter of the 18th century. The process of origin and development of spiritual and secular education in Siberia is characterized. The study was carried out on the basis of an analysis of the decrees of Peter I published in the Complete Collection of Laws of the Russian Empire, which regulate the organization of educational institutions in Siberia. A number of clerical sources of the Russian State Archive of Ancient Acts, in particular, the cases of the Siberian Order, are analyzed. Also, to study the topic, materials from the newspaper “Tobolsk Gubernskie Vedomosti” were involved. The authors of the article show that Peter’s modernization processes in the field of education were reflected in the life of the Siberian province in the first quarter of the 18th century. It is concluded that the main changes that affected the field of education are associated with the implementation of the reforms of Peter I. The role of the first theological schools in the education system of the Siberian province, the significance of the decrees of Peter I and the activities of the Orthodox Church in their formation are considered. At the same time, it is proved that the political events and cultural innovations of the Petrine era contributed to the formation of secular education and the spread of enlightenment among Siberians.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".