Financial Feeling: An Investigation of Emotion and Communication in the Workplace

There is growing interest in the role of emotion when considering communication in the workplace. This work has most often considered workers in front-line service positions in investigations of emotional labor, and human service workers in investigations of empathy and emotional work. In this study, we consider processes of both emotional labor and emotional work in the financial planning profession. Financial planners occupy a role requiring ongoing relationships with clients, conversations about the often emotional topic of money, and a need to manage emotion in a variety of interaction contexts. Thus, from extant theory and literature regarding emotion and communication, we proposed research questions regarding the roles of emotional labor and emotional work in the financial planning profession. These questions were investigated in a web-based survey study of almost 300 professional financial planners and supporting interviews with 14 financial planners. Results indicate support for existing theory on emotional work, extensions to current research regarding emotional labor, and important implications for the role of emotion and communication in a range of professional service roles.     

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.     

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.