Minh Nguyen

Fostering tolerance and inclusiveness in multicultural societies is increasingly vital, particularly in educational settings. Understanding the impact of parental involvement and school events on students’ attitudes toward these values is essential for promoting social cohesion and preparing future generations for an interconnected world. This study applies Bayesian Mindsponge Framework (BMF) analytics to a representative dataset of 2,069 primary, secondary, and high school students across Vietnam. It explores how parental discussions and participation in multicultural school events influence students’ attitudes toward tolerance and inclusiveness. The findings indicate that parental discussions about collaboration with individuals holding diverse perspectives, as well as participation in multicultural events, are positively associated with students’ tolerant attitudes. Furthermore, parental discussions about cultures and histories of different countries, collaboration skills, and conflict resolution skills are positively linked to students’ inclusiveness. The study highlights that while multicultural school events provide valuable opportunities for students to engage with diverse cultures and broaden their perspectives, consistent parental involvement through meaningful discussions is likely critical for reinforcing inclusive values. A collaborative approach between schools and parents can more effectively nurture tolerance and inclusiveness among students. Future research could examine the long-term effects of these interactions and identify specific activities that most effectively foster inclusive attitudes

Tourism education plays a key role in shaping students’ engagement with sustainability by providing them with the knowledge and skills to address environmental challenges and encouraging them to promote sustainable practices in the industry. This study explores how four years of tourism education at Prince of Songkla University in Phuket, Thailand, influence students’ knowledge, attitudes, and intentions toward sustainability. Despite gaining theoretical knowledge of sustainability principles, the findings reveal a decline in students’ willingness to adopt environmental sustainability practices as their years of education increase. This may reflect a disconnect between classroom lessons and practical application, potentially due to limited practical learning experiences and the prevalent “eco-deficit culture” within the tourism industry, which often prioritizes profit over environmental responsibility. As a result, students may filter out information regarding environmental sustainability despite their sustainability education at the university. To support long-term engagement in sustainability, the paper recommends revising curricula to include more experiential learning opportunities, interdisciplinary collaboration, and stronger partnerships with industry stakeholders.

This paper summarizes the evolution of analytic philosophy in Taiwan, examines its impact within and beyond academia, and discusses the future of the discipline. The roots of modern philosophy in Taiwan can be traced back to the Japanese colonial era, and analytic philosophy was introduced to the country in the late 1940s when many intellectuals in China moved to Taiwan. However, massive curbs were imposed on philosophy during Chiang Kai-shek’s dictatorship, and the discipline began to thrive again only after Taiwan’s democratization in the late 1980s. Nonetheless, since its introduction in the colonial era, modern philosophy has made significant contributions in Taiwan, encouraging interdisciplinary engagements, advancing civic education, and promoting the spirit of democracy and political liberation. Philosophy has played a key role in Taiwan’s remarkable transformation from an island colonized for hundreds of years to a country that recognizes democracy, freedom, and human rights. The themes of anti-colonialism and anti-domination seen in the works of modern Taiwanese philosophers not only reflect the discipline’s political and historical underpinnings but also signal how Taiwanese philosophy can acquire a distinct identity despite being influenced by many other philosophical traditions. While still at a nascent stage, Taiwanese philosophy has the potential to join forces with other philosophical traditions in advancing the vision of decolonizing philosophy.

Natural language processing techniques contribute more and more in analyzing legal documents recently, which supports the implementation of laws and rules using computers. Previous approaches in representing a legal sentence often based on logical patterns that illustrate the relations between concepts in the sentence, often consist of multiple words. Those representations cause the lack of semantic information at the word level. In our work, we aim to tackle such shortcomings by representing legal texts in the form of abstract meaning representation, a graph-based semantic representation that gains lots of polarity in NLP community recently. We present our study in AMR Parsing and AMR-to-text Generation specifically for legal domain. We also introduce JCivilCode, a human-annotated legal AMR dataset which was created and verified by a group of linguistic and legal experts. We conduct an empirical evaluation of various approaches in parsing and generating AMR on our own dataset and show the current challenges. Based on our observation, we propose our domain adaptation method applying in the training phase and decoding phase of a neural AMR-to-text generation model. Our method improves the quality of text generated from AMR graph compared to the baseline model. 2018; and “Legal Text Generation fromMeaning Representation”, published in the 32nd International Conference on Legal Knowledge and Information Systems 2019.).

We present our method for tackling a legal case retrieval task by introducing our method of encoding documents by summarizing them into continuous vector space via our phrase scoring framework utilizing deep neural networks. On the other hand, we explore the benefits from combining lexical features and latent features generated with neural networks. Our experiments show that lexical features and latent features generated with neural networks complement each other to improve the retrieval system performance. Furthermore, our experimental results suggest the importance of case summarization in different aspects: using provided summaries and performing encoded summarization. Our approach achieved F1 of 65.6% and 57.6% on the experimental datasets of legal case retrieval tasks.

This paper investigates the task of reference resolution in the legal domain. This is a new interesting task in Legal Engineering research. The goal is to create a system which can automatically detect references and then extracts their referents. Previous work limits itself to detect and resolve references at the document targets. In this paper, we go a step further in trying to resolve references to sub-document targets. Referents extracted are the smallest fragments of texts in documents, rather than the entire documents that contain the referenced texts. Based on analyzing the characteristics of reference phenomena in legal texts, we propose a four-step framework to deal with the task: mention detection, contextual information extraction, antecedent candidate extraction, and antecedent determination. We also show how machine learning methods can be exploited in each step. The final system achieves 80.06 % in the F1 score for detecting references, 85.61 % accuracy for resolving them, and 67.02 % in the F1 score for the end-to-end setting task on the Japanese National Pension Law corpus.

Introduction. This study examines differences in students’ perceived value of three artmaking modalities and whether the resulting creative projects offer similar or different insights into medical students’ professional identity formation. Methods. Mixed-methods design using a student survey, student narrative comments and qualitative analysis of students’ original work. Results. Poetry and comics stimulated insight, but masks were more enjoyable and stress-reducing. All three art modalities expressed tension between personal and professional identities. Discussion. Regardless of type of artmaking, students express concern about encroachments of training on personal identity but hoped that personal and professional selves could be integrated.

Rare Disease research has seen tremendous advancements over the last decades, with the development of new technologies, various global collaborative efforts and improved data sharing. To maximize the impact of and to further build on these developments, there is a need for model consent clauses for rare diseases research, in order to improve data interoperability, to meet the informational needs of participants, and to ensure proper ethical and legal use of data sources and participants’ overall protection. A global Task Force was set up to develop model consent clauses specific to rare diseases research, that are comprehensive, harmonized, readily accessible, and internationally applicable, facilitating the recruitment and consent of rare disease research participants around the world. Existing consent forms and notices of consent were analyzed and classified under different consent themes, which were used as background to develop the model consent clauses. The IRDiRC-GA4GH MCC Task Force met in September 2018, to discuss and design model consent clauses. Based on analyzed consent forms, they listed generic core elements and designed the following rare disease research specific core elements; Rare Disease Research Introductory Clause, Familial Participation, Audio/Visual Imaging, Collecting, storing, sharing of rare disease data, Recontact for matching, Data Linkage, Return of Results to Family Members, Incapacity/Death, and Benefits. The model consent clauses presented in this article have been drafted to highlight consent elements that bear in mind the trends in rare disease research, while providing a tool to help foster harmonization and collaborative efforts.

This article addresses the problem of automatically extracting legal indices which express the important contents of legal documents. Legal indices are not limited to single-word keywords and compound-word keywords, they are also clause keywords. We approach index extraction using structural information of Japanese sentences, i.e. chunks and clauses. Based on the assumption that legal indices are composed of important tokens from the documents, extracting legal indices is treated as a problem of collecting chunks and clauses that contain as many important tokens as possible. Each token is assigned a weight which is a statistical score, e.g. TF–IDF and Okapi BM25, to indicate its importance. The importance of a chunk or clause is determined based on the average weight of tokens included in that chunk or clause. Then, highly weighted chunks and clauses are recognized as the indices for legal documents. The experimental results on Japanese National Pension Act data show that our proposed method achieves better performance than TextRank, the most popular unsupervised method in extracting single-word and compound-word keywords. In addition, this approach is also applicable to extract clause keywords with high performance.