Impact of Emotional-Volitional Sphere of Future Specialists of Risky Professions on Professional Training Performance
Bibliographic record
Abstract
Objective: The professional activities of specialists of risky professions are carried out in extreme conditions, characterized by a significant number of stressful factors, which, if the professional qualities of specialists are not sufficiently developed, leads to a decrease in the efficiency of performance of official duties, professional burnout, and psychosomatic disorders. Background: The success of the performance of service tasks is primarily influenced by the developmental level of the emotional-volitional sphere, in particular self-regulation, emotional-volitional stability, ensuring the ability to make autonomous decisions, form and determine tasks following the requirements of complex, changing situations, and therefore, achieve their goals. The article aims to analyze the emotional and volitional state of future specialists of risky professions during training. Method: The leading research method was observation. The emotional-volitional sphere is an integral part of the system of regulating activity as a professional. During the research, the main areas of the formation of the emotional-volitional sphere were identified. With the help of psychological analysis, the important properties of future specialists in the development of the emotional-volitional sphere have been determined. Results: The analysis results show that future specialists have an average and low level of stylistic possibilities for self-regulation (modeling, programming, autonomy). The reasons for the low progress of future specialists have been determined. Conclusion: The practical significance of the research lies in the development of recommendations for training and the formation of the emotional-volitional sphere during educational activities.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".