Criminal-legal regulation of combating domestic violence: national experience and international approaches
Bibliographic record
Abstract
This article analyzes the criminal-legal regulation of combating domestic violence in Ukraine and international practice. It examines the application of Article 126-1 of the Criminal Code of Ukraine, which establishes criminal liability for systematic domestic violence, and identifies challenges in law enforcement. The study highlights difficulties in proving «systematicity» as a mandatory element of the crime, which complicates the prosecution of offenders in cases of isolated acts of physical or psychological violence. The article also explores the complexity of distinguishing Article 126-1 of the Criminal Code of Ukraine from other criminal law provisions, particularly Article 125 (intentional minor bodily harm) and Article 126 (battery and torture), which leads to legal uncertainty and complicates judicial practice. A comparative legal analysis of foreign approaches to combating domestic violence is conducted. It is established that countries such as France, Spain, and Poland have distinct criminal offenses that encompass various forms of violence, including physical, psychological, sexual, and economic abuse. Meanwhile, in countries such as the United States, Canada, and Austria, domestic violence is prosecuted under general provisions on violent crimes, albeit with consideration of the victim’s special status. Particular attention is given to the implementation of protective orders, the criminalization of stalking, the introduction of rehabilitation programs for offenders, and the systematic collection of data on violent crimes, which is mandatory in many European Union and North American countries. The study assesses the law enforcement practices in Ukraine, particularly the issues of inconsistent classification of domestic violence by courts, which results in significant discrepancies in judicial decisions and allows offenders to evade criminal liability. The necessity of legislative improvements is substantiated, including the revision of the «systematicity» requirement in Article 126-1 of the Criminal Code of Ukraine, the expansion of grounds for the immediate removal of offenders from the family, the precise definition of criteria for qualifying physical violence, and the strengthening of interagency coordination among law enforcement agencies, social services, and judicial institutions. The article proposes the adaptation of effective foreign mechanisms for combating domestic violence to Ukrainian legislation to enhance the protection of victims, improve mechanisms for holding offenders accountable, and refine the prevention system.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".