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6:00 pm - 7:00 pm CST
July 28, 2024
"Faculty hiring and the spread of scientific ideas"
University faculty play a special role in society: they make new discoveries and they train new generations of scientists. Despite their societal importance, inequalities within the scientific workforce, at both individual and institutional levels, are pervasive and persistent, and their consequences for science and society remain poorly understood.
This talk will answer two closely related questions about the composition and dynamics of the scientific workforce, using comprehensive data on roughly 250,000 tenured and tenure-track faculty, spanning all U.S. PhD-granting universities and all fields, including economics. First, we consider the question of who hires whose graduates as faculty and how the induced faculty hiring network can and does shape the production and spread of scientific ideas. Second, we consider the question of social representation and persistence in the scientific workforce, and how the induced composition may shape both the type of scholarship the workforce produces and the new scholars it trains. I will close by offering a challenge to the audience, to consider what discoveries and innovations we may be systematically losing due to these patterns, and how we might mitigate them in order to broaden our contributions to society.
Aaron Clauset is a Professor in the Department of Computer Science and the BioFrontiers Institute at the University of Colorado Boulder, and is External Faculty at the Santa Fe Institute. He received a PhD in Computer Science, with distinction, from the University of New Mexico, a BS in Physics, with honors, from Haverford College, and was an Omidyar Fellow at the prestigious Santa Fe Institute. He was awarded the Erdos-Renyi Prize in Network Science in 2016, and was named a Fellow of the Network Science Society in 2023. Since 2017, he has been a Deputy Editor responsible for the Social, Computing, and Interdisciplinary Sciences at Science Advances.
Clauset is an internationally recognized expert on network science, data science, and machine learning for complex systems. His research program is around two general themes: identifying fundamental principles of the organization and behavior of complex social and biological systems, and developing approaches for using data and computation to illuminate those ideas. A recent major focus of this work has been on the "science of science," where he studies the shape, origins, and consequences of social and epistemic inequalities on scientific careers, productivity, the spread of ideas, and the composition of the scientific workforce. His research results have appeared in many prestigious scientific venues, including Nature, Science, PNAS, SIAM Review, Science Advances, Nature Communications, and Physical Review Letters. His work has been covered in the popular press by Quanta Magazine, the Wall Street Journal, The Economist, Discover Magazine, Wired, the Boston Globe and The Guardian.