Ways of Forming Personal and Social-Labour Functions of a Future Teacher
Bibliographic record
Abstract
Objective: The relevance of research is determined by the fact that it allows identifying the main criteria by which the development of a teacher is ensured both at the level of personal development and at the level of improving labour functions. The authors understand the complex development of personal and social-labour functions of a teacher as self-development in the process of fulfilling professional relations. Background: Each of the participants in the educational process must meet the requirements set by state educational standards. With that, the personal qualities of a teacher should be fully correlated with the necessity of improving labour parameters. Method: The effectiveness of the introduction of pedagogical conditions, which had a significant impact on the professional self-development of teachers, was tested experimentally with the use of anthropocentric and activity-based approaches to studying the problem, as well as with the use of the statistical method. Results: The analysis presented in the paper showed that the indicated pedagogical conditions contribute to the formation of professional motivation, focus on the professional self-development of teachers, a high level of aspirations, awareness of the value of individual professional self-development, the ability to notice shortcomings, develop social skills and communication skills of teachers. Conclusion: It was determined that the socio-psychological climate in an institution, where there is organisational support from the administration and informational support from other specialists, contributes to the development of operational-activity and reflective and value-based components.
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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".