Computational Social Science Seminar: Daniel Larremore, University of Colorado Boulder
The Scientific Ecosystem: Hierarchy, Filtration, and Emergent Coordination
Abstract
The scientific enterprise is shaped by social processes that determine who does the science, where it gets published, and how it gets evaluated. This talk examines three of these processes drawing on network science, statistical inference, and adaptive surveys. First, using an annual census of US tenure-track faculty, we trace careers from hiring and promotion to mid-career moves and attrition, quantifying the roles of prestige, productivity, interdisciplinarity, and gender. Prestige hierarchies prove sticky, and faculty who move face a systematic tradeoff between prestige and promotion. Second, using all 110,303 submissions to Science and Science Advances over five years, we model editorial and peer review as a multistage filter and measure the influence of editors, reviewers, and idiosyncrasy. These results motivate a set of proposed experiments aimed at causal identification and better peer review. Third, using an adaptive survey of 3,510 faculty (163,000 pairwise comparisons across 8,044 venues), we investigate emergent coordination and consensus in publication preferences. Fields span a wide spectrum, from strong consensus in economics and chemistry to fragmented preferences in computer science and engineering, with systematic variation by prestige and gender.
About the CSS seminar series
The University of Michigan School of Information’s Computational Social Science seminar series brings together a vibrant and diverse community of scholars whose cutting-edge research in information science, computer science and the social sciences aims to broaden our understanding of important social and technological issues.
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Featured Speaker
Daniel Larremore
University of Colorado Boulder
Dr. Daniel Larremore is the Associate Chair for Research and an Associate Professor in the Department of Computer Science and core faculty in the BioFrontiers Institute at the University of Colorado Boulder. He is also an affiliate of the Department of Applied Mathematics at the University of Colorado Boulder, is a member of the external faculty at the Santa Fe Institute, and is a co-Founder and co-CEO of Cevian Labs. His research develops mathematical methods using novel combinations of networks, dynamical systems, and statistical inference to solve problems in two main areas: infectious disease epidemiology and computational social science. Prior to joining the University of Colorado faculty, he was an Omidyar Fellow at the Santa Fe Institute 2015-2017 and a post-doctoral fellow at the Harvard T.H. Chan School of Public Health 2012-2015. He obtained his Ph.D. in Applied Mathematics from the University of Colorado Boulder in 2012, and holds an undergraduate degree in Chemical Engineering from Washington University in St. Louis. He is the recipient of the Erdős–Rényi Prize from the Network Science Society and the Alan T. Waterman Award from the National Science Foundation.
Contact: [email protected]