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Abstract: Faculty hiring and retention determine the composition of the U.S. academic workforce and directly shape educational outcomes, career trajectories, the development and spread of ideas, and research priorities. But patterns in faculty hiring and retention are dynamic, reflecting societal and academic priorities, generational turnover, and long-term efforts to diversify the professoriate along gender, racial, and socioeconomic lines. In this talk, we'll analyze, at unprecedented scale and resolution, the academic employment and doctoral education of tenure-track faculty at all PhD-granting U.S. universities over the decade spanning 2011-2020, quantifying stark inequalities in faculty production, prestige, retention, gender, and country of training.

These analyses reveal universal inequalities in which a small minority of institutions supply a large majority of faculty, with hiring flows following steep hierarchies of prestige. Beyond hiring, we identify markedly higher rates of attrition for faculty (i) trained at U.S. universities that produce few faculty in general, (ii) trained outside the U.S., or (iii) employed by their doctoral alma mater. Critically, we show that across nearly all disciplines, and all career stages, rates of attrition are higher (and rates of promotion are lower) for women vs men. We unpack these patterns through a complementary analysis of survey responses from around 10,000 U.S. tenure-track faculty respondents, who told our research team about the stresses they experience in the academic workplace. Our work suggests that the steady gains in women's representation over the past decade are unlikely to result in long-term gender parity in most fields without substantial continuing efforts.

Bio: Dan Larremore is an Assistant Professor in the Department of Computer Science and 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, and is a member of the external faculty of the Center for Communicable Disease Dynamics at the Harvard T. H. Chan School of Public Health. 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. In 2022, he received the Alan T. Waterman Award from the National Science Foundation for his foundational research in computational epidemiology. Learn more about the Larremore Lab at

  • Mohammad Jubair
  • Ted Larremore
  • Raegan Rychecky
  • Ananya Ganesh

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