Labour Socialization of Young People in Today’s Russia: The Specificity of Sociological Discourse
Bibliographic record
Abstract
The paper considers the problem of labour socialization in the light of theoretical approaches, ideas and concepts existing in scientific literature. This problem is one of the most topical in modern Russian sociology of youth. The socialization of modern Russian society deals with various risks and hazards which form a crisis background for the labour socialization of Russian youth. While being studied this background causes different viewpoints to the development of professional values of young people, the specificity of their self-determination and behaviour in work sphere. The authors suppose that, at the level of sociological reflection, it is essential to develop alternative methodological strategies to study youth labour socialization, the state of main labour education agents of Russian young generation and the reconstitution strategy for the efficient system of labour socialization. This system should become a basis for moral and spiritual development of young people and labour potential of the country. The theory of creativity is an important methodological base for the study of labour socialization of young people in the author’s concept. This theory determines the essence of a perfect labour socialization model for youth. If implemented, it can promote not only the efficient labour socialization of Russian young generations but also the swift modernization of Russian society.
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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 | 0.004 | 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 | 0.007 | 0.015 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".