Государственная политика в области подготовки педагогических кадров в СССР в послевоенные годы
Bibliographic record
Abstract
The changes that took place in the last quarter of the 20th century in the political, economic and cultural life of Russia necessitated the modernization of the modern educational system. In this regard, an appeal to the experience of the past seems very relevant. The author considers main directions and tasks of the state policy in the field of teachers training in the post-war period as an integral part of the five-year plans for the development of the national economy of the country. The main sources of research are the documents of the State Archive of the Republic of Buryatia. Published sources on the history of school education in Buryatia and the history of the Buryat-Mongolian State University also played a great role in revealing the topic. Using the example of Buryatia the author establishes that pedagogical education, which is in dire need of teachers and schools, developed in accordance with all state guidelines. The development and strengthening of the material and technical base, the high level of scientific and pedagogical qualifications of the teaching staff of the Buryat-Mongolian State Pedagogical Institute, its constant interaction and cooperation with public education authorities were important conditions for the Institute to fulfill its main task – the quality training of teachers for general education schools in Buryatia.
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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 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.006 |
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".