Systematic inequality and hierarchy in faculty hiring networks

By Aaron Clauset, Samuel Arbesman, Daniel B. Larremore. Science Advances, 2015

565 citations recorded by the source corpus.

An analysis of networks of graduate-to-faculty hires reveals systematic hiring biases and patterns. The faculty job market plays a fundamental role in shaping research priorities, educational outcomes, and career trajectories among scientists and institutions. However, a quantitative understanding of faculty hiring as a system is lacking. Using a simple technique to extract the institutional prestige ranking that best explains an observed faculty hiring network—who hires whose graduates as faculty—we present and analyze comprehensive placement data on nearly 19,000 regular faculty in three disparate disciplines. Across disciplines, we find that faculty hiring follows a common and steeply hierarchical structure that reflects profound social inequality. Furthermore, doctoral prestige alone better predicts ultimate placement than a U.S. News & World Report rank, women generally place worse than men, and increased institutional prestige leads to increased faculty production, better faculty placement, and a more influential position within the discipline. These results advance our ability to quantify the influence of prestige in academia and shed new light on the academic system.

Subfields: Sociology and Political Science, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/6db769b3cbb3d7237a45561c818b4c0cc1d9b4e3

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In Sociology and Political Science

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  3. Paul K. Piff
  4. Daniel A. McFarland
  5. Paul E. Smaldino
  6. Dan Jurafsky
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In Statistics and Probability

  1. Vincent Larivière
  2. João M. Santos
  3. Daniel A. McFarland
  4. An Zeng
  5. Jianlin Zhou
  6. Paul E. Smaldino
  7. Dan Jurafsky
  8. Jinshan Wu

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