Development of Integrity and Intolerance to Corruption in the System of Preparation for Military Service
Bibliographic record
Abstract
The urgency of the issue of the development of integrity and intolerance to corruption in the system of preparation for military service is becoming increasingly publicised, since the number of such negative social phenomena, manifested in the form of abuse of power or official position to obtain illegal material benefits, is constantly growing, which as a result provokes an imbalance in the main paramilitary structures of Ukraine, in particular the Armed Forces of Ukraine. The purpose of this study is to analyse the current systems of educating socially positive qualities that are necessary to prevent the spread of corruption, to highlight their disadvantages and solutions that will help to overcome them. This research aimed at studying the sphere of military security and integrity of officers who are the personnel of military bodies was conducted using such methods as logical analysis, comparative analysis, the formal-legal, synthesis, deduction, analysis of scientific literature. The result of this study is to identify and highlight the theoretical and practical foundations of the mechanism of educating socially important qualities and intolerance to corruption in the military during preparation for military service, their effectiveness in affirming in the minds of each officer the main principles and foundations for countering abuse of power and obtaining benefits of various kinds. The research is aimed at developing and educating intolerance to corruption and other socially dangerous phenomena in preparing for military service, since in the future this may lead to a decrease in the authority of a particular structure and in the level of trust in it from the population, the introduction of methods that will improve and make such preventive systems more effective.
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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 | 0.004 | 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 | 0.005 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.004 |
| 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".