Books are silent ambassadors: The Noma award for the translation of Japanese literature

Summary Now more than ever good translations are proving to be vitally important to fulfilling Shoichi Noma’s mission of advancing good relationships between cultures. With the emergence of dozens of world-class Japanese writers, the translators of Japanese literature have acquired a new significance and a new importance. No longer are they required to simply handle the language like an exotic and precious commodity but they must prepare a writer’s work to compete with literature from around the globe and let others understand the issues at their very heart of the Japanese people. Indeed, the selection committee’s choice of Murakami’s Wind-Up Bird Chronicle is an apt example of how literature at its very best can span cultural divides to promote mutual understanding of very complicated and important world issues. Written for Japanese to help them understand the devastation of war, it is a rare and timely book that confronts Japan’s experience head on. Ironically, Noma’s idea that books are silent ambassadors, an idea born from agony and defeat, so many years later is helping the world come together towards a unified vision of peace and understanding. “Literature has been described as a means of exchange between the hearts of people. Literary translation, then, is the building of bridges so that all peoples of the world can interact in this way.” Ye Weiqu, Chinese Institute of Social Studies.     

Creating Access to Invisible Special Collections: Using Participatory Management to Reduce a Backlog

The University of Colorado at Boulder Libraries used participatory management to reduce a special collections backlog. Without an increase in budget or staffing, technical and public services departments designed a pilot project to redeploy internal human resources in a collaborative manner. The process of backlog management is discussed.     

Academic health sciences library Website navigation: an analysis of forty-one Websites and their navigation tools.

BACKGROUND: The analysis included forty-one academic health sciences library (HSL) Websites as captured in the first two weeks of January 2001. Home pages and persistent navigational tools (PNTs) were analyzed for layout, technology, and links, and other general site metrics were taken. METHODS: Websites were selected based on rank in the National Network of Libraries of Medicine, with regional and resource libraries given preference on the basis that these libraries are recognized as leaders in their regions and would be the most reasonable source of standards for best practice. A three-page evaluation tool was developed based on previous similar studies. All forty-one sites were evaluated in four specific areas: library general information, Website aids and tools, library services, and electronic resources. Metrics taken for electronic resources included orientation of bibliographic databases alphabetically by title or by subject area and with links to specifically named databases. RESULTS: Based on the results, a formula for determining obligatory links was developed, listing items that should appear on all academic HSL Web home pages and PNTs. CONCLUSIONS: These obligatory links demonstrate a series of best practices that may be followed in the design and construction of academic HSL Websites.     

Analysis of Statistical Question Classification for Fact-Based Questions

Question classification systems play an important role in question answering systems and can be used in a wide range of other domains. The goal of question classification is to accurately assign labels to questions based on expected answer type. Most approaches in the past have relied on matching questions against hand-crafted rules. However, rules require laborious effort to create and often suffer from being too specific. Statistical question classification methods overcome these issues by employing machine learning techniques. We empirically show that a statistical approach is robust and achieves good performance on three diverse data sets with little or no hand tuning. Furthermore, we examine the role different syntactic and semantic features have on performance. We find that semantic features tend to increase performance more than purely syntactic features. Finally, we analyze common causes of misclassification error and provide insight into ways they may be overcome.