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arXiv · 2602.12188

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·Andrés R. Vindas-Meléndez
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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 from nationally reported degree data, allowing postdoctoral and faculty dynamics to be examined under completion, exit, and hiring processes. Advancement to faculty positions is modeled as vacancy limited, with competition for permanent positions depending on downstream population size. Numerical simulations show that increases in degree inflow do not translate into proportional faculty growth when hiring is constrained by limited turnover. Instead, excess supply accumulates primarily at the postdoctoral stage, leading to sustained congestion and elevated competition. Sensitivity analyses indicate that long run workforce outcomes are governed mainly by faculty exit rates and hiring capacity rather than by degree production alone. These results demonstrate the central role of vacancy limited hiring in shaping academic career trajectories within the field of the mathematical sciences.

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Oluwatosin Babasola, Olayemi Adeyemi, Ron Buckmire, Daozhou Gao, Maila Hallare, Olaniyi Iyiola, Deanna Needell, Chad M. Topaz, Andrés R. Vindas-Meléndez. 2026-02-12. A Discrete-Time Model of the Academic Pipeline in Mathematical Sciences with Constrained Hiring in the United States. https://arxiv.org/abs/2602.12188

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