Predicting the Success of Mediation Requests Using Case Properties and Textual Information for Reducing the Burden on the Court

The success of mediation is affected by many factors, such as the context of the quarrel, personality of both parties, and the negotiation skill of the mediator, which lead to uncertainty for the predicting work. This paper takes a different approach from previous legal prediction research. It analyzes and predicts whether two parties in a dispute can reach an agreement peacefully through the conciliation of mediation. With the inference result, we can know if the mediation is a more practical and time-saving method to solve the dispute. Existing works about legal case prediction mostly focus on prosecution or criminal cases. In this work, we propose a LSTM-based framework, called LSTMEnsembler, to predict mediation results by assembling multiple classifiers. Among these classifiers, some are powerful for modeling the numerical and categorical features of case information, e.g., XGBoost and LightGBM; and, some are effective for dealing with textual data, e.g., TextCNN and BERT. The proposed LSTMEnsembler aims to not only combine the effectiveness of different classifiers intelligently, but also capture temporal dependencies from previous cases to boost the performance of mediation prediction. Our experimental results show that our proposed LSTMEnsembler can achieve 85.6% for F-measure on real-world mediation data.

Locomotor skill acquisition in virtual reality shows sustained transfer to the real world

Background Virtual reality (VR) is a potentially promising tool for enhancing real-world locomotion in individuals with mobility impairment through its ability to provide personalized performance feedback and simulate real-world challenges. However, it is unknown whether novel locomotor skills learned in VR show sustained transfer to the real world. Here, as an initial step towards developing a VR-based clinical intervention, we study how young adults learn and transfer a treadmill-based virtual obstacle negotiation skill to the real world. Methods On Day 1, participants crossed virtual obstacles while walking on a treadmill, with the instruction to minimize foot clearance during obstacle crossing. Gradual changes in performance during training were fit via non-linear mixed effect models. Immediate transfer was measured by foot clearance during physical obstacle crossing while walking over-ground. Retention of the obstacle negotiation skill in VR and retention of over-ground transfer were assessed after 24 h. Results On Day 1, participants systematically reduced foot clearance throughout practice by an average of 5 cm (SD 4 cm) and transferred 3 cm (SD 1 cm) of this reduction to over-ground walking. The acquired reduction in foot clearance was also retained after 24 h in VR and over-ground. There was only a small, but significant 0.8 cm increase in foot clearance in VR and no significant increase in clearance over-ground on Day 2. Moreover, individual differences in final performance at the end of practice on Day 1 predicted retention both in VR and in the real environment. Conclusions Overall, our results support the use of VR for locomotor training as skills learned in a virtual environment readily transfer to real-world locomotion. Future work is needed to determine if VR-based locomotor training leads to sustained transfer in clinical populations with mobility impairments, such as individuals with Parkinson’s disease and stroke survivors.

A proposed model for effective negotiation skill development

Purpose Previous research on negotiation skills has focused mostly on the negotiation itself and tactics used when bargaining, while little research has examined the process by which people become effective negotiators. The purpose of this paper is to develop an initial model from an intra-organizational perspective to outline the factors that contribute to the development of negotiation skills and behaviors by employees. Design/methodology/approach This conceptual paper relies on prior research and existing theory to focus on the types of developmental and learning experiences and processes that lead to the acquisition of three specific types of key negotiation skills and behaviors. Findings Distributive, integrative, and adaptable negotiation skills are developed most effectively via different learning and development activities, respectively. Additionally, unique individual difference and situational variables could contribute to particular negotiation behaviors, either directly or via an interaction with developmental experiences. Practical implications The paper proposes a model for future testing in which results can provide support for tailored/customized training and development of employee negotiation skills. Providing the correct people with the correct tools in the correct manner is always desirable by practitioners. Originality/value This proposed holistic model provides new insights, structure, and suggestions for more research on factors that lead to negotiation skill development and exhibition of effective negotiation behaviors. This paper goes beyond description of negotiation tactics and addresses the various negotiation contexts and the unique skills needed for each. Most importantly, the paper addresses how those skills are uniquely and most effectively developed.