Culture-forming language role and knowledge of students of the national language in polyethniche regions
Bibliographic record
Abstract
In article author studies of the process of the national, ethnic and cultures formation of the school students in poly-ethnic regions during longitude from 1989 till present time in in Astrakhan, Barnaul, Groznyy, Ivanovo, Krasnodar, Maikop, Makhachkala, Moscow, Nazran', Nalchick, Pskov, Stavropol. We prepare analysis of the views, positions and motivation of the activity of the young persons. During of the international project «Dialogue Partnership as the Factor of Stability and Integration» («Bridge between East and West») and Program «Young in Poly-Ethnic Regions: Views, Positions, Orientations» we prepare non stop monitoring (longitude) for studies as school boys know ethnic language, what is motivation for this studies and possibility for using. Results of the surveys during of the Program «Young in Poly-Ethnic Regions: Views, Positions, Orientations» have approbation in the International Forums: World Congress of the Political Science (Berlin, 1994), World Sociological Congress (Montreal, 1998, Toronto, 2018), Russian Sociological Congresses (2000, 2008), Forum «Young Generation — Not Frontier Life» (2011), UNESCO Forum «Dialog as Way to пониманию» (2013), Week of the Science and Education (2017).
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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 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".