Collaborative Research: New Methods to Enhance Our Understanding of the Diversity of Science

合作研究：增强我们对科学多样性理解的新方法

• 批准号: 0965364
• 负责人: Fiona Murray
• 金额: $ 24.83万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-05-15 至 2014-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0965364&HistoricalAwards=false
• 关键词: Collaborative; Research; New; Methods; Enhance

This project focuses on the development and implementation of new quantitative methods to provide a deeper understanding of science policy interventions. By building analytic tools that capture the diversity of science, this project moves beyond existing methods that typically analyze the rate of scientific innovation. This move is an important next step in the "science of science policy" agenda:Intellectual Merit: Although understanding of institutional changes on the rate of inventive activity has improved markedly in recent years, effective science policy interventions must also be grounded in an understanding of their impact on diversity as well as productivity, construed both in terms of idea diversity -- the array of different ideas derived from novel scientific insights -- and individual diversity -- the variety of people and organizations in social space engaged in scientific progress. To move forward with this crucial agenda requires a rich new set of tools. In developing such tools, this project extends prior work that focuses on "citation-counting," combining novel approaches from social and computer sciences to represent and analyze publication, patent and grant data in idea and social space. Specifically, the tools integrate two powerful methods: (a) statistical topic modeling and (b) social network analysis. Broader Impact: These methods can also be extended to examine diversity across national, social and topic boundaries, thus providing quantitative tools to characterize issues of key significance in debates over national competitiveness. While these science policy questions could be addressed in a wide variety of settings, this project focuses on the varied data associated with the human genome and human genetics.

该项目的重点是开发和实施新的定量方法，以更深入地了解科学政策干预措施。通过构建捕捉科学多样性的分析工具，该项目超越了通常分析科学创新率的现有方法。这一举措是“科学政策的科学”议程的重要下一步：尽管近年来对制度变化对发明活动率的影响的理解有了显著提高，但有效的科学政策干预还必须立足于对多样性和生产力的影响的理解，从思想多样性--从新颖的科学见解中产生的一系列不同的思想--和个人多样性--社会空间中从事科学进步的各种人和组织来解释。为了推进这一关键议程，需要一套丰富的新工具。在开发这些工具时，该项目扩展了以前的工作，重点是“引用计数”，结合社会科学和计算机科学的新方法来表示和分析思想和社会空间中的出版物，专利和赠款数据。具体来说，这些工具集成了两种强大的方法：（a）统计主题建模和（B）社交网络分析。更广泛的影响：这些方法还可以扩展到审查跨越国家、社会和专题界限的多样性，从而提供量化工具，在关于国家竞争力的辩论中描述具有关键意义的问题。虽然这些科学政策问题可以在各种各样的环境中得到解决，但该项目侧重于与人类基因组和人类遗传学相关的各种数据。