The Silk Road of Science- IPL Speaker Series

 

We develop a new framework to study the development and autonomy of national scientific enterprises. Our method applies machine learning models to author information on 4.4 million scientific articles involving international collaboration to identify the project leaders (as opposed to the supporting actors) of each article. Aggregating leaders to their countries-of-residence allows us to determine the hierarchical position of power of each country in the global collaboration network. We use our framework to analyze recent changes in the hierarchical position of Chinese science. We begin by focusing on the hierarchical nature of collaborations between Chinese and U.S. scientists, and find that China substantially narrowed its gap behind the U.S. in scientific leadership between 1995 and 2021. Extending this trend, we predict that China will reach parity with the U.S. in terms of scientific leadership in 2033. Next, we show that China is achieving scientific leadership more quickly in other parts of the world. Delving into administrative documents, we uncover how China is extending the reach of its scientific enterprise beyond its territorial borders by investing in and training young scientists in regions that have been relatively neglected by Western science, particularly in Central Asia and Sub-Saharan Africa. As a consequence, China now enjoys a strong leadership position in collaborations with scientists from these regions, and engages scholars from these regions to produce research that advances China’s own strategic interests. We conclude that the narrowing of the China-U.S. leadership gap and the strong leadership position China has established in much of Asia and Africa indicate that China’s scientific enterprise is sophisticated and territorially distributed. As a consequence, policymakers in the U.S. and other Western countries have less leverage in affecting China’s scientific development than is commonly believed.

 

 

Chris Esposito is a postdoctoral fellow at UCLA’s Anderson School of Management, where he is also associated with the Price Center for Entrepreneurship and Innovation. He was previously a postdoctoral fellow at the Mansueto Institute for Urban Innovation and the Knowledge Lab at the University of Chicago. His research studies how newcomers can break into and succeed in the innovative economy, despite the odds stacked against them. He studies these opportunities at multiple scales, from individual inventors and organizations, to larger and more complex units of coordination, including cities and countries. His dissertation analyzed 170 years of data to understand how new cities in U.S. grew to become centers for innovation and economic prosperity, even when they had few local advantages to spur local growth in their earliest years. His more recent research studies related processes at the individual and national levels, using causal identification methods, machine learning approaches, and long-run panel microdata.