Information Support of Youth Policy as a Factor of Formation of the Social Capital and Political Attitudes of the Young Generation
Bibliographic record
Abstract
If we sum up the tasks facing the Russian state in relation to the young generation, then all of them are associated with its harmonious inclusion in the social and political development of the country. At the normative level, the current need is declared for young people to form active citizenship and democratic political culture, which is possible only in a constant and equal dialogue between the authorities and young people. Ensuring the interaction of the younger generation with the political elite presupposes the existence of certain conditions - the creation and effective functioning of the information infrastructure of youth policy, as well as the conduct of an open active information policy. The article describes the results of a study of the political status of students of the capital of Tatarstan - Kazan, in particular, such parameters as youth interest in political information, trust in the sources of this information, and political participation. Together with the data of secondary studies, this made it possible to characterize the youth sector of political communication, identify the existing difficulties in the interaction of the government and youth, in particular, identify some difficulties in receiving and disseminating political information among the youth, which impede the development of a democratic political culture and the accumulation of social capital of the young generation.
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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 | 0.004 |
| 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 | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".