Health-saving competence as a component of the professional culture of a teacher: peculiarities of formation in martial law conditions
Bibliographic record
Abstract
The article deals with the peculiarities of forming a teacher's health-saving competence under martial law. It is emphasized that health-saving competence is an important component of the professional culture of a modern teacher. Based on the analysis of the professional standards of developed countries, in particular the USA, Great Britain, Canada, Germany and Poland, it is shown that this competence is integral for teachers. In the context of martial law, such a component of health competence as the ability to maintain physical and mental health in the course of professional activity is actualized. Ukrainian teachers should be able to monitor both their own physical and mental health and the health of their students; respond to negative changes in a timely and adequate manner, and think of ways to overcome crisis situations. A teacher who is not able to be conscious of his or her own physical and mental resources is unlikely to be able to teach students to live a healthy lifestyle and to follow the rules of hygiene, including mental hygiene. In order to develop teachers' health-saving competence, a set of measures combining theory and practice is proposed. The activities are part of the educational and methodological environment "Development of Pedagogical Culture" based on the website of the official website of Kremenchuk Gymnasium No. 1 of the Kremenchuk City Council of Kremenchuk District, Poltava Region. The development of a set of measures was carried out in response to requests from teachers, as the problem of preserving the physical and mental health of teachers has become much more acute due to the full-scale aggression. Air raids and rocket attacks, blackouts, constant anxiety about relatives who have joined the ranks of the Armed Forces – all this has a negative impact on the condition of teachers. Individual consultations with psychologists are not available due to financial constraints and lack of time, so organizing effective psychological and pedagogical activities at the gymnasium that take into account the wishes of the participants seems to be an effective way to build the health competence of teachers under martial law.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".