Search Results (316)

The rule of law can be considered as a multidimensional institutional phenomenon, which emerges through interplay between legal, governance and administrative institutions. The paper offers an exploratory statistical modeling approach to find empirical patterns in national rule-of-law profiles according to the 2024 World Justice Project (WJP) Rule of Law Index. Eight dimensions of the index are considered to identify differences between countries and similarities of their multidimensional institutional performance. Principal Component Analysis reveals strong associations between eight dimensions, which are structured along the same performance institutional scale; the first principal component explains 85.7% of the overall variation and two principal components explain 92.5% of it. K-Means, hierarchical and DBSCAN clustering methods are then used to examine the empirical similarities between countries. While the six-cluster solution of K-Means offers distinct group descriptions, low bootstrap stability of this solution suggests that these groups cannot be regarded as fixed rule-of-law regimes. In addition, the Random Forest analysis reveals Regulatory Enforcement, Absence of Corruption, and Criminal Justice as the three dimensions, which contribute to the empirical differentiation of the described profiles the most. In general, the results imply that international variations in rule-of-law performance are viewed as heterogeneous locations in a multidimensional institution space, rather than as stable and distinct legal systems. The above-presented methodology allows for an exploratory approach to analyze international variations in rule-of-law performance that considers the limitations of cross-section data and instability of clusters. Full article

Microbial forensics has beneficial characteristics for investigating crimes. Law and order are fundamental to any nation and carry significant responsibilities. Failure in this domain may result in wrongful convictions or the guilty remaining free. Key duties include managing criminal cases and addressing threats to public order. While identifying the culprit, establishing their connection to the crime is paramount. Since legal systems require evidence for conviction, law enforcement increasingly relies on advancing scientific methods to meet this need. For example, in this case, after applying conventional techniques like DNA analysis and fingerprinting, a new technique, such as microbial forensics or fingerprints, can be applied. Trace evidence can be in the form of microbial fingerprints, and this evidence can play an important role in solving the crime. Microbial communities are dense and active in living and non-living things and in the environment. The classification and roles of these bacterial populations could be used as markers. The distinction between forensic samples is achievable because there is a diversity of microbial communities found in the human body from one location to another, and even in identical twins. The specific microbiome, which can be found on the skin or in specific body areas, may precisely identify the suspect’s connection with the crime scene for the purposes of human identification. This paper discusses the objects and latest advancements in the science of microbial forensics and their significance within the law enforcement process. Full article

Forensic genetics is moving from locus-based DNA profiling toward genome-wide inference enabled by high-density single-nucleotide polymorphism (SNP) data. While short tandem repeats remain central to routine human identification, SNP-based technologies and massively parallel sequencing have expanded the analysis of distant kinship through detection of identity-by-descent (IBD) segments and shared autosomal DNA. This narrative review synthesizes the biological basis of SNP-based distant kinship inference, the statistical and computational frameworks used to model genomic relatedness, and the operational transition from relatedness detection to forensic genetic genealogy (FGG). It distinguishes genetic genealogy database matching from formal forensic kinship testing, targeted SNP panels, SNP capture, low-coverage sequencing, Bayesian and machine-learning approaches, and independent forensic confirmation. Applications in criminal investigations, unidentified human remains, historical identifications, and broader relationship-inference contexts are discussed. The review also examines limitations related to recombination, stochastic inheritance, marker density, genotype quality, degraded or mixed forensic samples, population structure, endogamy, database composition, and genealogical record availability. Ethical and regulatory issues involving consent, privacy, database governance, law-enforcement access, data retention, and non-consenting relatives are considered. Overall, SNP-based forensic genomics can generate powerful investigative leads, but its outputs must be interpreted within method-specific analytical and evidentiary boundaries. Full article

The use of artificial intelligence chatbots that mirror human interaction and emotional closeness has given rise to new forms of crime. Traditional online grooming is generally conceptualized as an offence in which a human perpetrator plans, initiates, and executes criminal conduct. However, the increasing involvement of artificial intelligence has introduced novel and complex scenarios. AI systems may either autonomously engage in conduct that facilitates the sexual exploitation of children or serve as tools that enhance, automate, or scale offenders’ activities. These developments challenge the traditional understanding of the offence and expose significant gaps in existing legal frameworks. Consequently, current regulatory approaches may prove inadequate to address the evolving nature of AI-assisted online grooming and associated forms of child sexual exploitation. This study investigates the case of grooming via social media using AI chatbots and discusses whether the current criminal legislation is sufficient to address this offence. Through a legal comparative method, this study examines the legal rules in the European Union, the United Kingdom, the United States, and China, focusing on the elements of criminal acts and criminal intent and the consideration of the liability of platform operators, developers, and deployers of AI systems. The study also discusses the problem of intermediary liability rules and less mature AI governance policies to tackle the fragmented and hidden nature of algorithmic actions. The study concludes that existing criminal law frameworks face significant challenges in addressing AI-assisted grooming, particularly regarding criminal intent, foreseeability, and liability allocation. The fragmentation of responsibility among offenders, platforms, and AI developers creates regulatory and enforcement gaps in the law. Accordingly, this study advocates for a risk-based liability framework, enhanced platform accountability, greater algorithmic transparency, and stronger child-centered safeguards. Full article

In the modern understanding of public administration, public authorities establish companies governed by private law to ensure flexibility and efficiency in service delivery. However, the fact that these companies utilize public funds necessitates effective oversight in accordance with the principles of accountability and transparency. Since the capital of these companies is derived from public resources, their financial auditing by public authorities becomes necessary. Under Turkish law, the financial audit of these companies—established with public capital and whose managers are appointed by public authorities—is carried out by the institution known as the Turkish Court of Accounts (TCA). This study aims to analyze the structure and functioning of the TCA, the institution responsible for the financial audit of public companies, within the framework of the Turkish Court of Accounts Act No. 6085, and to provide an overview of this subject. Based on the TCA Act, the body responsible for assessing the financial discipline and legal compliance of public companies is introduced. This study also provides information on the public officials serving within the TCA and the units in which they perform their duties. Furthermore, it addresses the disciplinary and criminal liability of those serving within the TCA. Full article

This article examines the legal inadequacy of traditional piracy frameworks in responding to contemporary maritime threats. The legal definition of piracy, rooted in Articles 101 and 105 of the United Nations Convention on the Law of the Sea (UNCLOS), was designed for a narrower category of maritime violence than now exists, and this definitional gap produces enforcement failures across criminal, international, and maritime governance law. Drawing on interdisciplinary literature spanning maritime security, criminology, international law, cybersecurity, and organised crime research, the article identifies five principal threat categories that fall outside existing piracy law: organised maritime crime, maritime terrorism, cyber-enabled disruption, illegal fishing, and state-linked hybrid maritime activity. It further identifies structural legal vulnerabilities, including jurisdictional fragmentation, the high seas/territorial waters divide, the private gain requirement, and the absence of a unified cyber–maritime legal instrument, that prevent existing frameworks from adequately regulating contemporary maritime criminality. The article concludes with a normative argument for an expanded, adaptive legal framework integrating cybersecurity, grey zone activity, and organised crime into maritime law, alongside improved international coordination, intelligence-sharing obligations, and governance capacity. The paper contributes directly to ongoing debates about the fitness for purpose of UNCLOS and the need for supplementary legal instruments to address twenty-first-century maritime threats. Full article

Sharia and Law colleges in Saudi universities provide a distinctive educational setting in which classical Islamic jurisprudential discourse and contemporary statutory legal discourse coexist within the same curriculum. Despite this shared institutional context, the pragmatic characteristics of these coexisting normative genres remain largely unexplored from a corpus-based perspective. This study examines how genre differences influence the linguistic formulation of legal definitions and religious rulings across four officially prescribed texts: two classical Hanbali works—Rawḍat al-Nāẓir by Ibn Qudāma and Al-Rawḍ al-Murbiʿ by al-Buhūtī—and two contemporary Saudi statutes—the Civil Transactions Law and the Law of Criminal Procedure. A purpose-built corpus of approximately 480,000 words was analysed using a corpus-assisted discourse analysis design integrating quantitative frequency and keyword analysis with systematic manual pragmatic coding within a triangulated theoretical framework. The findings show that differences in disciplinary genre are systematically reflected in distinct pragmatic profiles. Rawḍat al-Nāẓir is characterised by assertive-definitional speech acts and methodological deontic expressions, whereas Al-Rawḍ al-Murbiʿ is dominated by directive speech acts associated with applied legal rulings. The statutory texts employ standardised legislative constructions, including negative-exceptive formulations, formal prohibition markers, and institution-specific obligation structures. The Civil Transactions Law further exhibits a hybrid pragmatic register through the incorporation of classical jurisprudential maxims into enacted statutory provisions. Based on the systematic literature review undertaken for this study, the findings provide what is, to the best of the authors’ knowledge, the first corpus-based pragmatic comparison of these coexisting curricular genres. The study thereby contributes to Arabic legal linguistics, corpus pragmatics, and the linguistic analysis of legal education, while offering empirically grounded insights for curriculum development in Sharia and Law programmes. Full article

The development of large artificial intelligence models relies on the integrity and accuracy of training data. Malicious contamination of training data introduces false information. This information becomes fixed as parameter bias during model training. Consequently, it affects judgment logic and model output. Therefore, data contamination has become a primary method for attacking the security of large models. Despite this threat, legal regulations concerning data poisoning lack systematic research. This paper employs a normative analysis method. It systematically reviews regulatory rules regarding data poisoning. These rules are found within Chinese criminal and data security laws. Current legislation primarily enforces general data security duties. It also relies heavily on accountability after an incident occurs. This approach makes early intervention difficult. Risks often evolve into model defects and cause damage before effective measures are taken. Therefore, the main contribution of this paper is moving beyond the current retrospective regulation model. We advocate establishing a risk control mechanism for the entire training process. This mechanism spans from prior review to continuous monitoring and subsequent accountability. Furthermore, it clearly divides the responsibilities among four main entities. These entities include data providers, model developers, service providers, and regulatory agencies. This mechanism helps resolve practical difficulties associated with data poisoning. These challenges include multiple participants, complex causal relationships, and unclear responsibilities. The proposed framework responds to the genuine needs of data security. It aligns with the governance goal of improving hierarchical and classified security supervision. Ultimately, it provides a feasible analytical framework for protecting training data. Full article

Recidivism remains a persistent challenge in criminal justice systems because data are fragmented across jurisdictions, privacy laws are stringent, and legal definitions of recidivism vary. This thematic literature review synthesizes evidence on risk factors influencing recidivism, traditional and centralized artificial intelligence and machine learning (AI/ML) approaches, explainable AI (XAI) for transparency and bias auditing, generative AI for local data augmentation, and federated learning in privacy-sensitive environments. The review identifies recurring patterns, including improved ensemble performance on balanced datasets and increased use of XAI for bias auditing, while also highlighting persistent limitations related to methodological variation, privacy constraints, jurisdictional heterogeneity, and fairness concerns. Based on these findings, Recid-Fed is proposed as a conceptual research agenda to guide future research on privacy-preserving and jurisdiction-aware recidivism prediction. Rather than presenting an implemented system, this paper consolidates the current literature and outlines the key research requirements that should be addressed in future framework development and empirical validation studies. Full article

This article provides a comprehensive overview of the case law of the European Court of Justice related to the rebuttal of the principle of mutual trust in the process of judicial cooperation in criminal matters. It analyses ten judgements of the Court, which were delivered in preliminary ruling procedures that concerned the ground for refusal—established by the Court in its jurisprudence, hence referred to as unwritten ground—in cases when the execution of the judicial decision would have possibly jeopardised the protection of fundamental rights. This article provides a thorough analysis of the cases, shedding light on the gradual extension of the scope of the unwritten refusal ground, the Court’s resolve to protect the original structure of the Aranyosi test, the exceptional derogations from this resolve, and the various procedural aspects of carrying out the Aranyosi test. It argues that the rules governing the application of the unwritten refusal ground have been clarified, so much so that they may be ready to be translated into secondary legislation. As such, the aim of this article is to provide a legislative proposal for implementing the unwritten refusal ground into secondary sources of EU law based on the case law analysis. Full article

(1) Background: The digital traces of unmanned aerial vehicles (UAVs) are becoming increasingly important in criminal incidents, the violation of airspace and in military operations, thus making the reconstruction of the digital traces a critical task. But, current tools like DatCon, Autopsy and GRYPHON cannot recover telemetry when the flight logs are logically damaged, fragmented or partially deleted and don’t offer any quantitative measurement of the confidence of the recovered information. (2) Methods: A unified hardware-software complex, including a forensic workstation, a hardware write-blocker and SD/microSD/eMMC adapters; a set of software modules for extracting artifacts from files, structural parsing of DAT/BIN/CSV log, neural network reconstruction of missing telemetry using a two-layer LSTM architecture; a multi-source correlation module that combines flight logs, telemetry, media metadata and controller artifacts; a module, Confidence Score (CS), that computes a reliability measure in $[0,1]$; and a visualization module to generate a reconstructed trajectory on an electronic map. (3) Results: The complex has been tested on 105 flights on 10 different UAVs, 492 flight logs were gathered, 10,435 were the media item files and 624 GB was the amount of storage during acquisition. The carving stage recovers 98.7% of artifacts across the eight signature classes, the LSTM module recovers all five telemetry parameters with $R^2>0.99$ and a single-step horizontal position error of 6.8 m, which is reduced to 4.7 m after multi-source correlation (below the 5 m operational target consistent with consumer-GNSS precision); the dependence on gap length is described by the empirical growth law ${\epsilon }_{\mathrm{horiz}}\approx 4.84·G^{1.44}$ m; 46.8% of recovered records fall within the high-confidence band of $\mathrm{CS}\ge 0.8$; and the complex outperforms DatCon, Autopsy + DJI Analyzer and GRYPHON by 22–35 percentage points in end-to-end record recovery and by a factor of ∼2.6 in mean horizontal error (4.7 m vs. 12.4–18.7 m). (4) Conclusions: The combined write-blocked hardware acquisition, neural reconstruction of telemetry, and quantitative confidence index provides a forensically structured pipeline that fills an existing gap in UAV digital forensics; we note that technical reconstruction accuracy does not by itself confer legal admissibility, which remains a function of jurisdiction-specific evidentiary standards discussed in the Conclusions. Full article

To date, many studies on the Nazi Special Courts have focused on the individuals involved in passing judgement or in the prosecution process in general, as well as on their political significance. For our study, we undertake a re-evaluation and computational ‘upcycling’ of an archive catalogue from the 1970s containing around 10,000 legal cases from the Munich Special Court (1933–1945). Although this was not an entirely new phenomenon–they were originally introduced by the Weimar Republic–, the Special Courts were unique in that they brought together general criminal law and ‘crimes’ in the form of non-conformity with National Socialist ideology under a single jurisdiction. Full article

Background: Recent technological advances, such as 3D laser scanning, digital photogrammetry and virtual autopsy, have significantly reshaped the acquisition and interpretation of scientific evidence in criminal proceedings. These tools enable highly detailed visualizations that can enhance factual understanding while also introducing potential cognitive biases for judges. This study aims to assess the legal, epistemological and forensic implications of 3D virtual reconstruction as evidence, examining its admissibility, scientific robustness, and associated risks within contemporary criminal trials. Methods: An interdisciplinary methodology was applied, integrating criminal procedural law, forensic medicine, digital forensics and legal epistemology. The study includes doctrinal analysis, a review of the literature from the last decade, Italian and comparative case law, and evaluation of European forensic guidelines (particularly ENFSI). Direct observation of laboratory practices and technical assessment of reconstruction tools were conducted to evaluate scientific validity, repeatability, traceability and transparency. Results: The findings reveal that 3D reconstruction provides high metric accuracy, durable digital preservation of the crime scene and improved communication of complex dynamics to the court. It allows experts to test alternative hypotheses, reducing ambiguity in technical explanations. Nevertheless, several critical issues emerged: the persuasive power of highly realistic imagery, dependence on non-transparent software processes, potential vulnerabilities in the chain of custody for digital data, and the absence of a unified Italian regulatory framework governing digital scientific evidence. Conclusions: 3D virtual reconstruction constitutes a powerful but epistemologically complex form of scientific evidence. Its probative value depends on transparent methodology, verifiability and strict compliance with adversarial safeguards. The study underscores the need for national technical standards, clear admissibility criteria and specialized training for legal professionals. A coherent regulatory framework is essential to ensure that digital technologies enhance, rather than distort, the pursuit of truth in criminal justice. Full article

China’s legal system currently lacks a comprehensive animal protection law, and its Criminal Law contains no specific offense for animal cruelty. Consequently, judicial protection for companion animals relies on offenses designed to safeguard human interests, such as intentional destruction of property, theft, and releasing hazardous substances, manifesting a distinct characteristic of indirect protection. This study systematically reviews criminal cases to examine the current state of animal protection provided by Chinese criminal law, identifying the fundamental limitation that such protection is merely incidental or reflective. The research findings indicate that while current frameworks are human-centric, there is significant untapped potential within existing statutes. Specifically, this article advocates for utilizing the crime of illegal use of information networks and other relevant offenses to address the critical regulatory gap concerning the production, sale, and dissemination of animal torture media. This pragmatic solution offers a valuable reference for jurisdictions facing similar legislative voids where specialized animal protection laws are unlikely to be enacted in the short term, promoting a more effective utilization of existing criminal doctrines to safeguard animal welfare. Full article

This paper reports a systematic study of low-rank adaptation (LoRA)-based fine-tuning applied to Qwen3 language models (4B, 8B, and 14B parameters) for the task of legal question answering within the jurisdiction of the Republic of Kazakhstan. The bilingual dataset comprises 63,114 question–answer pairs (76.2% Russian, 23.8% Kazakh) covering 11 legal domains. Models are evaluated through both automated metrics (BERTScore, citation accuracy, and hallucination rate) and blind expert assessment by a panel of two practising legal experts. Key findings: (1) all fine-tuned models reach BERTScore F1 close to 90% (89.6–90.2%) versus 82.2–83.1% for untuned base models; (2) fine-tuned models outperform GPT-4o (87.2%) and GPT-4o-mini (86.7%) on semantic similarity while exhibiting far lower hallucination rates (27–29% vs. 83–90%); (3) blind expert assessment confirms the advantage of fine-tuned models, with panel mean completeness scores of 4.28/5 versus 1.95/5 for base models (quadratically weighted Cohen’s κ = 0.80–0.95 across rating dimensions, indicating substantial to almost perfect inter-rater agreement); and (4) we identify a practical scaling plateau: paired Wilcoxon tests (n = 500) detect statistically significant but practically small differences across the 4B, 8B, and 14B fine-tuned variants (largest mean gap 0.67 pp on BERTScore F1; Cohen’s |d_z| ≤ 0.34), gains too small to justify the 3.5× parameter increase. These findings show that parameter-efficient adaptation of compact open-source models can match or exceed commercial LLMs for specialised legal QA in a low-resource bilingual context. We note one scope restriction: three domains (administrative, criminal, and housing law) are represented only in Russian, so the model is not validated for Kazakh language queries in these areas. Full article