The need for a legal mechanism for creating attractive military companies as a component of the reintegration of military personnel into society
Bibliographic record
Abstract
Based on the analysis of the situation in Ukraine regarding the number of military personnel with combat experience and the need for their reintegration into society during the transition from military to civilian life after the war, as well as the analysis of foreign experience, the need to develop a legal mechanism for creating private military companies in Ukraine is substantiated. The current state of developing a legal mechanism for creating private military companies is analyzed, particularly scientific developments, draft laws submitted to the Verkhovna Rada of Ukraine, and conclusions. It is stated that in Ukrainian society and politics, there is an understanding of the need to legalize the activities of private military companies. At the same time, a legal mechanism for such activities has not yet been developed. When developing such a mechanism, special attention should be paid to the compliance of the activities of private military companies with the Constitution of Ukraine, as well as the norms of international and international humanitarian law. The provisions of the Montreux Document signed by Ukraine, The International Code of Conduct for Private Security Service Providers, documents of the United Nations, and the Organization for Security and Cooperation in Europe should be considered. It has been deemed appropriate to use the experience of the United States, Canada, Germany, and other countries, which successfully attracted former military personnel who participated in military operations to work in such companies when developing the mechanism for creating and operating the PMC. It is concluded that the creation and functioning of private military companies in Ukraine based on international and international humanitarian law using the existing human potential can become a significant factor in security while ensuring a comfortable transition from military to peaceful life for a substantial part of Ukrainian combatants, as well as additional financial revenues to the budgets of Ukraine. At the same time, insufficiently thought-out decisions in this area can have very negative consequences. Therefore, solving the difficult task of creating and functioning private military companies requires serious scientific research, which is highly insufficient in Ukraine.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".