Innovative research of the content of physical training of armed forces of foreign states as an element of training of military professional
Bibliographic record
Abstract
Keeping military units in constant combat readiness requires the leadership of the armed forces to find new approaches to the organization, structure and content of physical training. Research on the relationship between indicators of physical fitness of servicemen and their readiness to perform tasks assigned to them by domestic and foreign experts proves the need to improve the content of sets of tests of general and professionally applied physical fitness. The purpose of the study was to identify areas for improving the content of physical training in the armed forces of foreign countries to improve the combat readiness of servicemen. Research methods. Methods of theoretical analysis and generalization of scientific and methodological literature were used for the research. In total, more than 60 sources of information were analyzed, followed by a final review and 22 sources of literature, including 15 foreign authors, the material of which was processed using general scientific methods. Results. The study found that in the armed forces of NATO, the United States and Canada, physical fitness is considered one of the most important indicators of the readiness of personnel to perform professional tasks. One of the main strategies of physical training is to minimize the negative impact of real situation factors on the overall performance and combat readiness of personnel, which becomes especially important in conditions of long, continuous combat operations. Conclusions. The necessity of simplification of the domestic system of physical training with simultaneous substantiation of validity of tests for an estimation of the general and professionally applied physical fitness of military men is defined.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".