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Articles 1 - 3 of 3
Full-Text Articles in Education
Harry Flechtner--A True Teacher/Scholar, With Rhythm, Ronald A. Brand
Harry Flechtner--A True Teacher/Scholar, With Rhythm, Ronald A. Brand
Articles
This is a tribute to Professor Emeritus Harry Flechtner upon his retirement from the University of Pittsburgh School of Law. Professor Flechtner was a leading scholar on the United Nations Convention on Contracts for the International Sale of Goods (CISG), a stellar teacher, a musician who used that skill in the classroom as well as the Vienna Konzerthaus, and a genuinely nice person.
Exploring Diversity With A "Culture Box" In First-Year Legal Writing, Ann N. Sinsheimer
Exploring Diversity With A "Culture Box" In First-Year Legal Writing, Ann N. Sinsheimer
Articles
Studying law is in many ways like studying another culture. Students often feel as though they are learning a new language with unfamiliar vocabulary and different styles of communication. Throughout their legal education, students are also exposed to a profession comprised of unique traditions and expectations. As a result, learning law takes time and energy. It can be both engaging and frustrating and may even challenge some of students’ values and belief systems. To ease her students’ transition to law school, the author starts her course each year with a “culture box” exercise, which encourages students to examine who they …
Automatically Extracting Meaning From Legal Texts: Opportunities And Challenges, Kevin D. Ashley
Automatically Extracting Meaning From Legal Texts: Opportunities And Challenges, Kevin D. Ashley
Articles
This paper examines impressive new applications of legal text analytics in automated contract review, litigation support, conceptual legal information retrieval, and legal question answering against the backdrop of some pressing technological constraints. First, artificial intelligence (Al) programs cannot read legal texts like lawyers can. Using statistical methods, Al can only extract some semantic information from legal texts. For example, it can use the extracted meanings to improve retrieval and ranking, but it cannot yet extract legal rules in logical form from statutory texts. Second, machine learning (ML) may yield answers, but it cannot explain its answers to legal questions or …