A Discrete-Time Model of the Academic Pipeline in Mathematical Sciences with Constrained Hiring in the United States
Oluwatosin Babasola, Olayemi Adeyemi, Ron Buckmire, Daozhou Gao, Maila Hallare, Olaniyi Iyiola, Deanna Needell, Chad M. Topaz, Andr\'es R. Vindas-Mel\'endez

TL;DR
This paper presents a discrete-time model of the mathematical sciences academic pipeline, revealing how constrained hiring and faculty exit rates significantly influence career progression and workforce composition.
Contribution
It introduces a novel compartmental model linking degree data to faculty dynamics, emphasizing the impact of vacancy-limited hiring on academic career flow.
Findings
Increased degree inflow does not proportionally increase faculty numbers under hiring constraints.
Postdoctoral positions tend to accumulate excess supply, causing congestion.
Faculty exit rates and hiring capacity are key determinants of long-term workforce outcomes.
Abstract
The field of the mathematical sciences relies on a continuous academic pipeline in which individuals progress from undergraduate study through graduate training and postdoctoral program to long term faculty employment. National statistics report trends in bachelor's, master's, and doctoral degree awards, but these data alone do not explain how individuals move through the academic system or how structural constraints shape downstream career outcomes. Persistent growth in postdoctoral appointments alongside relatively stable faculty employment indicates that degree production alone is insufficient to characterize workforce dynamics. In this study, we develop a discrete time compartmental model of the academic pipeline in the field of the mathematical sciences that links observed degree flows to latent population stocks. Undergraduate and graduate populations are reconstructed directly…
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Taxonomy
TopicsDoctoral Education Challenges and Solutions · Higher Education Research Studies · Higher Education and Employability
