Judicial Intelligent Assistant System: Extracting Events from Divorce Cases to Detect Disputes for the Judge

In formal procedure of civil cases, the textual materials provided by different parties describe the development process of the cases. It is a difficult but necessary task to extract the key information for the cases from these textual materials and to clarify the dispute focus of related parties. Currently, officers read the materials manually and use methods, such as keyword searching and regular matching, to get the target information. These approaches are time-consuming and heavily depending on prior knowledge and carefulness of the officers. To assist the officers to enhance working efficiency and accuracy, we propose an approach to detect disputes from divorce cases based on a two-round-labeling event extracting technique in this paper. We implement the Judicial Intelligent Assistant (JIA) system according to the proposed approach to 1) automatically extract focus events from divorce case materials, 2) align events by identifying co-reference among them, and 3) detect conflicts among events brought by the plaintiff and the defendant. With the JIA system, it is convenient for judges to determine the disputed issues. Experimental results demonstrate that the proposed approach and system can obtain the focus of cases and detect conflicts more effectively and efficiently comparing with existing method.Comment: 20 page

Conservation and crime convergence? Situating the 2018 London Illegal Wildlife Trade Conference

The 2018 London Illegal Wildlife Trade (IWT) Conference was the fourth and biggest meeting on IWT convened at the initiative of the UK Government. Using a collaborative event ethnography, we examine the Conference as a site where key actors defined the problem of IWT as one of serious crime that needs to be addressed as such. We ask (a) how was IWT framed as serious crime, (b) how was this framing mobilized to promote particular policy responses, and (c) how did the framing and suggested responses reflect the privileging of elite voices? Answering these questions demonstrates the expanding ways in which thinking related to crime and policing are an increasingly forceful dynamic shaping conservation-related policy at the global level. We argue that the conservation-crime convergence on display at the 2018 London IWT Conference is characteristic of a conservation policy landscape that increasingly promotes and privileges responses to IWT that are based on legal and judicial reform, criminal investigations, intelligence gathering, and law enforcement technologies. Marginalized are those voices that seek to address the underlying drivers of IWT by promoting solutions rooted in sustainable livelihoods in source countries and global demand reduction. We suggest that political ecology of conservation and environmental crime would benefit from greater engagement with critical criminology, a discipline that critically interrogates the uneven power dynamics that shape ideas of crime, criminality, how they are politicized, and how they frame policy decisions. This would add further conceptual rigor to political ecological work that deconstructs conservation and environmental crime

Moral Systems in the Regulations of Nonprofits: How Value Commitments Matter

This essay explores how three behavior-shaping systems - legal, market, and moral - influence the fundamental tasks of both for-profit and nonprofit organizations, including organizational goal-setting; motivation of participants; and deterring and reducing abuse of power. After identifying key features of these normative systems and their characteristic differences, the author argues that the influence of moral systems on nonprofit organizations may be underestimated, especially in view of their potentially unifying role with respect to all of the fundamental tasks. He suggests that the prospects for effective reform of nonprofit governance and accountability regimes are improved when the mechanisms and effects of these moral systems are taken into account.This publication is Hauser Center Working Paper No. 33.6. Hauser Working Paper Series Nos. 33.1-33.9 were prepared as background papers for the Nonprofit Governance and Accountability Symposium October 3-4, 2006

Machine learning in predictive analytics on judicial decision-making

Legal professionals globally are under pressure to provide ‘more for less' – not an easy challenge in the era of big data, increasingly complex regulatory and legislative frameworks and volatile financial markets. Although largely limited to information retrieval and extraction, Machine Learning applications targeted at the legal domain have to some extent become mainstream. The startup market is rife with legal technology providers with many major law firms encouraging research and development through formal legal technology incubator programs. Experienced legal professionals are expected to become technologically astute as part of their response to the ‘more for less' challenge, while legal professionals on track to enter the legal services industry are encouraged to broaden their skill sets beyond a traditional law degree. Predictive analytics applied to judicial decision-making raise interesting discussions around potential benefits to the general public, over-burdened judicial systems and legal professionals respectively. It is also associated with limitations and challenges around manual input required (in the absence of automatic extraction and prediction) and domain-specific application. While there is no ‘one size fits all' solution when considering predictive analytics across legal domains or different countries' legal systems, this dissertation aims to provide an overview of Machine Learning techniques which could be applied in further research, to start unlocking the benefits associated with predictive analytics on a greater (and hopefully local) scale

An algorithm for modelling the impact of the judicial conflict-resolution process on construction investment

In this article, the modelling of the judicial conflict-resolution process is considered from a construction investor’s point of view. Such modelling is important for improving the risk management for construction investors and supporting sustainable city development by supporting the development of rules regulating the construction process. Thus, this raises the problem of evaluation of different decisions and selection of the optimal one followed by distribution extraction. First, the example of such a process is analysed and schematically represented. Then, it is formalised as a graph, which is described in the form of a decision graph with cycles. We use some natural problem properties and provide the algorithm to convert this graph into a tree. Then, we propose the algorithm to evaluate profits for different scenarios with estimation of time, which is done by integration of an average daily costs function. Afterwards, the optimisation problem is solved and the optimal investor strategy is obtained—this allows one to extract the construction project profit distribution, which can be used for further analysis by standard risk (and other important information)-evaluation techniques. The overall algorithm complexity is analysed, the computational experiment is performed and conclusions are formulated

Psychological, social and welfare interventions for psychological health and well-being of torture survivors

This is the protocol for a review and there is no abstract. The objectives are as follows: Primary objective 1. To assess beneficial and adverse effects of psychological, social and welfare interventions versus no treatment for the reduction of psychological distress in torture survivors. Secondary objectives 2. To describe the quality and generalisability of the studies evaluating the effects of these treatment approaches on torture survivors, and specifically: • to provide an objective assessment of risk of bias in these studies; • to describe the specific populations evaluated in studies of torture survivors (including demographics, torture experiences and psychological status); • to describe the variety of interventions that have been evaluated in these populations; and • to describe the outcomes evaluated in these intervention studies