Ethnocultural and Social Dominants of Pedagogical Education in Conditions of National Region
Bibliographic record
Abstract
Teacher education at the present stage of its development undergoes changes because of the processes of globalization in general plus the influence of the Bologna process. This diminishes the level of Russian pedagogical experience. For the country like Russia, with its diversity of languages, traditions, ethnicities and cultures the pedagogical traditions of peoples are of a great importance for the modern teacher education. The main idea of the article is that “the civic task of education and the education system is to give each one absolutely mandatory amount of human knowledge, which is the basis of self-identity of the people” (from an article by Vladimir Putin “Russia: the national question”). The purpose of this article is to identify and study of ethno-cultural and social dominants of teacher education in the national region. The main approaches in considering the Russian system of teacher education in the article are defined as: evolutionary, axiological, regional approaches which allow us to consider the teacher education as a cultural-historical and ethno-cultural phenomenon. As an example for the analysis and synthesis of the Russian teacher education in historical perspective and actual measurements two national republics of the Volga region—Mari El and the Chuvash Republics are taken.
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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 | 0.002 | 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 | 0.003 | 0.008 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| 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; 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".