Funding Agencies and the Formation of Innovative Subdisciplines

• In Event: Text-Based Machine Learning, Big Data, and the Social Study of Science - I

Abstract

Government funding agencies wield substantial influence on scientific research. They select the kinds of research topics, projects, institutions, and teams that receive funding. They direct billions of dollars into those selections. And they can amplify the impact of those awards by maintaining those preference for years. Sociologists conduct investigations of funding agencies and their effects on the social structures of science, but these studies have just begun to examine how funding agencies can foster the formation of innovative subdisciplines that span substantial disciplinary divides. In this paper, we focus on the US National Science Foundation. In particular, we look at the NSF's Broadening Participation portfolio, a collection of awards each of which aims partly to increase the number of underrepresented minorities in STEM fields. The NSF has spent hundreds of millions of dollars on this portfolio, which spans all of its directorates, in the previous 15 years. We focus on those awards that have been used to create K-12 education programs, and we show how researchers who received those awards comprise (or don't) collaboration networks, indicating the seeding of new subdisciplines. This work is based on computer assisted, but relatively low-tech, techniques to create large databases, find a subset of awards relative to research questions, find award-funded research outputs, and visualize collaboration networks. The protocols used to conduct this work can be redeployed to systematically address questions about funding agencies portfolios more generally.

Authors

• Steve Elliott, Arizona State University

• Hatem Al-Hattali, Arizona State University

• Elizabeth Wentz, Arizona State University

• Kimberly A. Scott, Arizona State University