Features of the Segmental Formation of Ukrainian Politics Under Martial Law
Bibliographic record
Abstract
The purpose of the study is to determine the format of the state policy of Ukraine in certain segments, considering the challenges of the legal regime of martial law by solving such research tasks as: defining measures of the legal regime of martial law and their praxeological significance for the formation of State Policy; Research Directions for reforming anti-corruption policy and their regulatory and institutional support; research on the state of policy transformation to ensure the rights of persons in places of deprivation of Liberty.The subject of the research is the priority vectors for certain segments of state policy, which are mediated by the action of the legal regime of martial law in Ukraine.The quality of implementation and provision of the declared ideas of national security will be reflected in all spheres of public relations, so it is important not to form, but to implement a policy in the field of national security.It is primarily important to formally reflect it in the approved anti-corruption strategy for the relevant period without reservations about the introduction of martial law in the state for the formation of an anti-corruption policy.As for the tightening of anti-corruption measures, in fact, the introduction of martial law has led to the imposition of tougher sanctions.It is established that in the conditions of the legal regime of martial law, among the rights of persons in places of deprivation of Liberty, a prominent place is given to ensuring the right to evacuation.The article analyzes the institutional mechanism and legal basis for the evacuation of persons in places of deprivation of Liberty.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".