Analysis of the testing system of overall and specific physical preparedness of firefighters in Serbia and abroad
Bibliographic record
Abstract
The aim of this study is to carry out a comparative analysis of different methodologies for testing the basic and specific physical preparation of firefighters that are applied in different countries of the world and, based on the application of the synthesis of knowledge, to provide a theoretical basis for the optimization and definition of the most adequate model of testing the fire service in the Republic of Serbia. Adequate levels of firefighting skills, physical abilities and energetic mechanisms of energy generation, contribute to reducing the risk of injuries and enable firefighters to resist the overall stress in the profession and to be efficient in specific task realization. Different countries worldwide have different methodologies for testing basic and specific physical preparedness of firefighters. Current testing systems implemented in the USA, Canada, Great Britain, Spain, Sweden and South Korea were analyzed. The analysis found that there is a significant correlation between the values of the basic and specific tests of the physical abilities of firefighters, with the fact that the specific tests are performed in complete personal protection. Based on the synthesis of applied tests and abilities in the analyzed countries, it was established that 24 tests are used to assess basic physical abilities, 14 for specific abilities and 29 for specific physical abilities. In accordance with the established results, it can be concluded that it is necessary to develop specific standardized test procedures for use throughout the fire service in Serbia. In addition to a more efficient assessment of specific physical preparedness, this would also enable control of the state of our firefighters through a more valid comparison of results, which would help in the development of normative data and new methodology needed for more efficient professionalization of the fire service. Established results imply that testing should be conducted biannually with the implementation of specific tests in complete personal protective equipment (PPE) with firefighting equipment. Also, it is necessary to enable adequate testing conditions for firefighters in smaller firefighting units in corresponding testing conditions with equipment.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".