Longitude studies of the patriotic mood of school youth in polyethnic regions (results of sociological surveys)
Bibliographic record
Abstract
The article considers the formation of the patriotic mood of school youth in polyethnic regions of the Russian Federation based on the data of large-scale longitude generational studies that have been conducted since 1998 and are unprecedented in scale for both Russian and Western research tradition. The surveys have been conducted in twelve regions: Astrakhan and the Astrakhan region, Groznyy, Ivanovo, Krasnodar, Maikop, Makhachkala, Moscow, Nazran, Nalchik, Pskov and Stavropol. The project focuses on the views and values of the younger generations, on their conflict and tolerance potential. The main goal of the project is to support the younger generations capable of confronting and overcoming life difficulties, of suppressing one’s negative and conflict reactions, of protecting one’s interests and respecting the interests of others, which would lead to the development of culture of tolerance and consent and to preventing xenophobia manifestations. For the study of ethnic-social attitudes, for the identification of conflict potential, for the prevention of conflicts and manifestations of xenophobia and extremism, the researchers developed an ethnic-conflict monitoring in the framework of the international project “Dialogue Partnership as a Factor of Stability and Integration” (“Bridge between East and West”) and the program “Youth of Polyethnic Regions: Views, Attitudes, Values” (the author is the founder and the head of the project and the program). The monitoring has been conducted for 29 years in the form of generational studies that aim to reveal the development of the youth ethnic consciousness in different regions, and to ensure a timely influence in order to reduce conflict potential and to support the culture of tolerance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".