Search Results (19)

In a strict legal sense, motive is often irrelevant in U.S. criminal law. Whether one smothered their grandmother with a pillow to ease her pain or to fraudulently collect her social security benefits, they are legally guilty of murder all the same. Yet anyone who has watched a courtroom drama or sat in the jury box knows the prominent role that establishing motive seems to play in influencing legal decision-makers. Why is motive so pivotal, so psychologically powerful for most people? We briefly review the existing literature on the psychology of motive, then introduce an adaptationist framework as a new lens for examining this question. In particular, we consider how motive assists perceivers in inferring actors’ welfare trade-off ratios, with important implications for legal judgments and willingness to punish. Full article

As large language models (LLMs) increasingly enter high-stakes decision-making contexts, questions arise about their suitability in domains requiring normative judgment, such as judicial sentencing. This study investigates whether LLMs exhibit bias when tasked with sentencing decisions in Polish criminal law, despite clear legal norms that prohibit considering extralegal factors. The simulated sentencing scenarios for theft offenses use two leading open-source LLMs (LLaMA and Mixtral) and systematically vary three defendant characteristics: gender, number of children, and the value of the stolen item. While none of these variables should legally affect sentence length under Polish law, our results reveal statistically significant disparities, particularly in how female defendants with children are treated. The non-parametric tests (Kruskal–Wallis and Mann–Whitney U) and correlation analysis were applied to quantify these effects. Our findings raise concerns about the normative reliability of LLMs and their alignment with principles of fairness and legality. From a jurisprudential perspective, we contrast the implicit logic of LLM sentencing with theoretical models of adjudication, including Dworkin’s moral interpretivism and Posner’s pragmatism. This work contributes to ongoing debates on the integration of AI in legal systems, highlighting both the empirical risks and the philosophical limitations of computational legal reasoning. Full article

Background and Objectives: Alcohol consumption has been a longstanding public health concern and known link to violence. The aims of this study were to analyze alcohol-related homicide cases in Lithuania, focusing on the prevalence of binge drinking among perpetrators and victims, the situational and behavioral patterns leading to violence, and the legal outcomes of these cases. Materials and Methods: This study employed a retrospective analysis of court case law of criminal cases of the year 2019. The analysis was conducted by combining qualitative and quantitative analytical approaches. Results: The findings revealed that 84.6% of homicides occurred during binge drinking events. Alcohol intoxication was prevalent among both perpetrators (92.3%) and victims (86.5%), emphasizing the dual role of alcohol in homicide cases. Interpersonal violence was the primary pattern of homicide (78.8%), while planned homicides accounted for 21.2%. Thematic content analysis of the cases revealed that Lithuanian courts consistently regard alcohol consumption as an aggravating factor that contributes to the commission of violent crimes and influences the severity of criminal punishment. This reflects a judicial position that voluntary intoxication does not lessen legal responsibility, despite its effects on impairing judgment, heightening aggression and impulsivity, and escalating conflicts into deadly violence. Conclusions: Our findings revealed that the majority of alcohol-involved homicides occurred during binge drinking events, in a domestic environment, and because of unplanned acts of interpersonal violence. Targeted public health interventions should focus on strengthening alcohol control policies and enforcing stricter regulations to discourage binge drinking environments. Full article

Legal judgment prediction is a common basic task in the field of Legal AI, aimed at using deep domain models to predict the outcomes of judicial cases, such as charges, legal provisions, and other related tasks. This task has practical applications in environmental law, including legal decision assistance and legal advice, offering a promising and broad prospect. However, most previous studies focus on using high-quality labeled data for strong supervised training in criminal justice, often neglecting the rich external knowledge contained in various charges and laws. This approach fails to accurately simulate the decision-making steps of judges in real scenarios, overlooking the semantic information in case descriptions that significantly impacts judgment results, leading to biased outcomes. In judicial environmental protection, the high overlap and similarity between different charges can cause confusion, and there is a lack of relevant judicial decision labeling datasets. To address this, we propose the External Knowledge-Infused Cross Attention Network (EKICAN), which leverages the robust semantic understanding capabilities of large models. By extracting information such as fact descriptions and court opinions from documents of criminal, civil, and administrative cases related to judicial environmental protection, we construct the Judicial Environmental Law Judgment Dataset (JELJD). We address data imbalance in this dataset using the text generation capabilities of judicial large models. Finally, EKICAN fuses semantic information from different parts with external knowledge to output prediction results. Experimental results show that EKICAN achieves state-of-the-art performance on the JELJD compared to advanced models. Full article

Prison sentences that exceed the natural lifespan present a puzzle because they have no more power to deter or incapacitate than a single life sentence. In three survey experiments, we tested the extent to which participants support these longer-than-life sentences under different decision contexts. In Experiment 1, 130 undergraduates made hypothetical prison sentence-length recommendations for a serious criminal offender, warranting two sentences to be served either concurrently or consecutively. Using a nationally representative sample (N = 182) and an undergraduate pilot sample (N = 260), participants in Experiments 2 and 3 voted on a hypothetical ballot measure to either allow or prohibit the use of consecutive life sentences. Results from all experiments revealed that, compared to concurrent life sentences participants supported the use of consecutive life sentences for serious offenders. In addition, they adjusted these posthumous years in response to mitigating factors in a manner that was indistinguishable from ordinary sentences (Experiment 1), and their support for consecutive life sentencing policies persisted, regardless of the default choice and whether the policy was costly to implement (Experiments 2 and 3). These judgment patterns were most consistent with retributive punishment heuristics and have implications for sentencing policy and for theories of punishment behavior. Full article

This essay brings psychoanalytic theory on trauma together with film and television criticism on rape narrative in an analysis of Michael Coel’s 2020 series I May Destroy You. Beyond the limited carceral framework of the police procedural, which dislocates the act of violence from the survivor’s history and context, Coel’s polyvalent, looping narrative metabolizes rape television’s forms and genres in order to stage and restage both trauma and genre again and anew. Contesting common conceptions of vulnerability and susceptibility that prefigure a violent breach of autonomy, Coel’s series and her interviews about it invite an ethics of looking that embraces a curiosity in the unknowable and untreatable kernel of subjective experience and defies and resists a policing of the survivor’s thoughts and emotions. By emphasizing and exploring what psychoanalysis calls the “afterwardness” of trauma, Coel foregrounds her main character’s subjectivity prior to her victimization, widens the sphere of consequence beyond the victim and criminal justice system to the survivor’s larger community, and entreats that community to preserve a space for her to look and look again at everything, without judgment. Full article

Child abuse has negative impacts on the well-being of children and often leads to adverse consequences, such as suicide, alcohol addiction, depression, and substance abuse. To better understand domestic child abuse in Taiwan, this study analyzed 73 criminal judgments (open-access documents) in which the victims of domestic child abuse were children below the age of 12 from the “Judicial Yuan Law and Regulations Retrieving System” database. There were 73 victims and 91 perpetrators involved. The results indicated that younger children were more likely to be victims of physical abuse, and the majority of death cases were committed by biological parents and cohabiting partners. The perpetrators tended to be young males with lower education. Male cohabiting partners appeared to be a high-risk population for child abuse. Approximately 63% of perpetrators experienced poverty, and 24.7% suffered from marital discord. In the 73 cases, 61.6% of the victims died, 21.9% were mildly injured, and 16.5% were severely injured. The sentencing was related to the level of injury, with perpetrators of mild injury sentenced to less than one year while perpetrators with victim death were sentenced to a longer period of imprisonment. It is suggested that parents at higher risk require greater financial and social support and should be educated on appropriate disciplinary techniques. Full article

It has been more than ten years since the nationwide sentencing standardization reform was implemented in China to solve the widespread problem of uneven sentencing in criminal justice. A statistical analysis of 1595 written judgments of illegal possession of drugs showed that the reform of sentencing for the standardization amount-based crimes has achieved remarkable results, and judges’ discretion has been highly normative and consistent. Under the same criminal circumstances, the degree of consistency between the amount involved in the crime and imprisonment has significantly increased, which is more in line with the standards of formal justice. However, the effect of the sentencing standardization reform declined as the amount involved in the crime increased. This exposes the shortcomings of the standardized sentencing model when considering multiple crimes; these include confusion between the amount and circumstances of a crime, the imbalance between crime and punishment, and the application of discretionary circumstances in sentencing depending on the amount involved in the crime. Therefore, it is necessary to attach more importance to the evaluation of the legitimacy of the sentencing range established by criminal law in subsequent sentencing reforms and to further refine and perfect the standardized sentencing mode, with a shift from formal justice to justice in form and substance. Full article

The increasing amount of legal information available online is overwhelming for both citizens and legal professionals, making it difficult and time-consuming to find relevant information and keep up with the latest legal developments. Automatic text summarization techniques can be highly beneficial as they save time, reduce costs, and lessen the cognitive load of legal professionals. However, applying these techniques to legal documents poses several challenges due to the complexity of legal documents and the lack of needed resources, especially in linguistically under-resourced languages, such as the Greek language. In this paper, we address automatic summarization of Greek legal documents. A major challenge in this area is the lack of suitable datasets in the Greek language. In response, we developed a new metadata-rich dataset consisting of selected judgments from the Supreme Civil and Criminal Court of Greece, alongside their reference summaries and category tags, tailored for the purpose of automated legal document summarization. We also adopted several state-of-the-art methods for abstractive and extractive summarization and conducted a comprehensive evaluation of the methods using both human and automatic metrics. Our results: (i) revealed that, while extractive methods exhibit average performance, abstractive methods generate moderately fluent and coherent text, but they tend to receive low scores in relevance and consistency metrics; (ii) indicated the need for metrics that capture better a legal document summary’s coherence, relevance, and consistency; (iii) demonstrated that fine-tuning BERT models on a specific upstream task can significantly improve the model’s performance. Full article

The rapid development of digital finance has changed all aspects of human life and has also had a deep impact on the social governance system. This paper constructs an unbalanced panel of data of the theft crime rates for 289 cities in China during 2014–2019 based on the theft criminal judgments published on China’s Judicial Documents website and explores the impact of digital financial inclusion on urban theft crime. It shows that there is a significantly negative correlation between digital financial inclusion and the urban theft crime rate, indicating that the development of digital financial inclusion can effectively reduce urban theft crime, which is also confirmed by instrumental variable analysis based on the spherical distance between cities and Hangzhou, and that digital financial inclusion mainly reduces theft crime committed by more serious and highly educated individuals. In addition, mechanism analysis shows that digital financial inclusion can reduce the expected benefits of theft by enhancing payment convenience and raise the opportunity cost by promoting employment. Therefore, in the Internet era, it is essential for China to continuously improve social governance tools that adapt to the development of new technologies to achieve high-quality urban development. Full article

The Croatian legislators introduced the concept of criminal liability for legal entities already in 2003 with the adoption of the Law on Criminal Liability of Legal Entities. Influenced by the writing of esteemed domestic scholars, and inspired by French law, the legislators opted for a system linking the liability of corporations to the liability of the responsible person. There were very few cases in practice during the first years of its application, and the situation changed after the first prominent indictment of this type against the ruling political party for economic crimes. Since then, the legislation has been amended several times and a significant body of jurisprudence has developed. In the first part of this paper, I will describe the chronology of the development and formation of the Croatian legislative model of corporate criminal liability. The second part will analyze 31 available final court judgments, which will be the basis for the conclusion about the issues in the practical application of the legislative model and, more generally, the phenomenon of criminal offenses committed by legal entities in Croatia. Based on this analysis, I will indicate the potential deficiencies of such a concept. In the context of future development, special attention will be given to the problem of economic crimes committed by AI corporate systems. Full article

Several cases of COVID-19-related mental disorders have emerged during the pandemic. In a case of femicide that occurred in Italy during the first phase of the pandemic, coinciding with a national lockdown, a discrepancy arose among forensic psychiatry experts, particularly toward the diagnosis of Brief Psychotic Disorder (BPD) related to COVID-19. We aimed to discuss the evaluation of the case through an integration of information and a literature review on comparable reported cases. An analysis of the diagnosis of brief acute psychosis was then performed, as well as a mini-review on cases of COVID-19-related psychosis. Results showed that psychotic symptomatology was characterized by polythematic delusions that always involved a SARS-CoV-2 infection. To a lesser extent, the delusions were accompanied by hallucinations, bizarre cognitive and associative alterations, insomnia, hyporexia, dysphoria, and suicidal behavior. No particularly violent acts with related injury or death of the victim were described. Finally, we could hypothesize that our case was better represented by a diagnosis of personality with predominantly narcissistic and partly psychopathic traits. The present case highlighted the importance, in the context of forensic psychiatry, of integrating assessments with the crime perpetrators, namely through accurate clinical interviews, neuropsychological tests, diachronic observations, and comparison with similar cases present in the literature. Such an integrated approach allows precise evaluation and reduces the odds of errors in a field, such as forensic psychiatry, where a diagnostic decision can be decisive in the judgment of criminal responsibility. Moreover, discerning forensics from health cases represents an important issue in risk management. Full article

Legal judgement prediction (LJP) is a crucial part of legal AI, and its goal is to predict the outcome of a case based on the information in the description of criminal facts. This paper proposes a decision prediction method based on causal inference and a multi-expert FTOPJUDGE mechanism. First, a causal inference algorithm was adopted to process unstructured text. This process did not require very much manual intervention to better mine the information in the text. Then, a neural network dedicated to each task was set up, and a neural network that simultaneously served multiple tasks was also set up. Finally, the pre-trained language model Lawformer was used to provide knowledge for downstream tasks. By using the public data set CAIL2018 and comparing it with current mainstream decision prediction models, it was shown that the model significantly improved the performance of downstream tasks and achieved great improvements in multiple indicators. Through ablation experiments, the effectiveness and rationality of each module of the proposed model were verified. The method proposed in this study achieved reasonably good performance in legal judgment prediction, which provides a promising solution for legal judgment prediction. Full article

The FER-R, Risk and Resource Assessment Form, is a multidimensional inventory of structured professional judgment that assesses criminogenic risks and resources for the design and management of individualized intervention plans with criminally sanctioned adolescents. The aim of this study was to examine the psychometric properties of the FER-R, reviewing its factorial structure to contribute evidence of convergent and discriminant construct validity in a sample of adolescents sentenced for crimes in Chile. For each domain (risks and resources) with its respective facets, a unidimensional bifactor structure (CFA-BF) was obtained, with adequate indices of fit that confirmed its construct validity, while the convergent validity was demonstrated with the YLS/CMI and the divergent validity with two MACI scales. The FER-R adds factorial validity to the evidence of the previously reported predictive validity, making it a robust inventory for the evaluation of young offenders, and a relevant tool to manage differentiated interventions in Chile, with a high potential for use in Latin America. The importance of finding a suitable balance in assessing risks and protective factors is discussed, in order to manage interventions adjusted to the needs of the adolescents to promote their criminal desistance. Full article