題目：Credibility and Use of Scientific and Technical Information in Policy Making
主講人：Jan Youtie副教授（佐治亞理工學院）
時間：2015年5月13日14:00--16:00
地點：主樓418
主講人簡介：
Jan Youtie博士是佐治亞理工學院經濟發展研究中心首席研究員，公共政策學院副教授，主要研究方向是新興技術評估、創新和知識的測量評估、基于科技的經濟發展、制造業競爭力。她是多個國際期刊的專門審稿人，先后主持和參與項目30余項，出版專著10本，發表學術論文30余篇，其文章“協調工業現代化服務：美國制造業拓展合伙關系的影響和分析”曾獲得美國Lang Rosen優秀論文金獎。
內容簡介：
We use text mining methods to analyze field structured data in journal publications and patents. But are these publications used in innovation policymaking? And how can we use our text mining methods to find this out? Many studies of the use of information in policymaking have been performed, but almost none look at the use of scientific and technical information and of these, most are based on anecdotes rather than quantitative information. This National Science Foundation project seeks to develop a new quantitative approach to examine the use of scientific and technical information (primarily journal articles) in reports of the National Academy of Science. The National Academy of Science serves as the “science advisor to the US Congress” so it could be argued that if scientific and technical information would be used anywhere, it would be used in National Academy of Science reports. In this project, we code the characteristics of these reports, committee members involved in writing the reports, cited references that are partially comprised of scientific and technical information, political system characteristics, and whether or not the National Academy of Science report is actually used by Congress. The results show that scientific and technical information is widely used in these reports, with use varying by policy area, year and size of the report, and sectoral affiliation of the authors of the report. However, reports with a substantial share of scientific and technical information are less likely to be used by Congress. In this seminar we will discuss the novel method used to obtain these findings and the benefits, as well as challenges and drawbacks of applying this text mining method to policy documents.
（主辦：管理工程系）
