Decoding University Hierarchy and Prestige in China through Domestic Ph.D. Hiring Network

2024-01-23

arXiv.org

AI Summary

This study investigates the implicit academic hierarchy and prestige固化 mechanisms embedded in China’s doctoral recruitment network among higher education institutions, focusing on the increasingly restrictive “credential ceiling” that impedes doctoral graduates’ mobility to higher-prestige institutions. Using employment records of nearly 28,000 PhD graduates over three decades, we construct a national doctoral hiring network among Chinese universities and— for the first time—apply the Minimum Violation Ranking algorithm to quantify latent institutional rankings. Integrating network analysis with large-scale educational employment data mining, we identify a cross-disciplinary, temporally stable hierarchical structure and a pronounced unidirectional concentration pattern in faculty mobility. Results confirm a persistent and intensifying consolidation of institutional prestige, providing critical empirical evidence to inform policies aimed at optimizing academic resource allocation and dismantling institutional barriers.

Technology Category

• Machine Learning: Learning Preferences or Rankings
• Constraint Satisfaction and Optimization: Constraint Learning and Acquisition
• Data Mining & Knowledge Management: Graph Mining, Social Network Analysis & Community

Application Category

• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking
• Graph Algorithms and Modeling for the Web: Algorithms and analysis for heterogeneous, signed, attributed, multi-relational, temporal, higher-order, and annotated Web-related graphs
• Web Mining and Content Analysis: Bridging structured and unstructured data

Abstract

The academic job market for fresh Ph.D. students to pursue postdoctoral and junior faculty positions plays a crucial role in shaping the future orientations, developments, and status of the global academic system. In this work, we focus on the domestic Ph.D. hiring network among universities in China by exploring the doctoral education and academic employment of nearly 28,000 scientists across all Ph.D.-granting Chinese universities over three decades. We employ the minimum violation rankings algorithm to decode the rankings for universities based on the Ph.D. hiring network, which offers a deep understanding of the structure and dynamics within the network. Our results uncover a consistent, highly structured hierarchy within this hiring network, indicating the imbalances wherein a limited number of universities serve as the main sources of fresh Ph.D. across diverse disciplines. Furthermore, over time, it has become increasingly challenging for Chinese Ph.D. graduates to secure positions at institutions more prestigious than their alma maters. This study quantitatively captures the evolving structure of talent circulation in the domestic environment, providing valuable insights to enhance the organization, diversity, and talent distribution in China's academic enterprise.

Problem

• Decoding hierarchy in China's university Ph.D. hiring network
• Analyzing imbalances in academic talent distribution across universities
• Measuring difficulty of graduates securing more prestigious positions

Innovation

• Analyzing Ph.D. hiring network with 28,000 scientists data
• Using minimum violation rankings algorithm for university hierarchy
• Quantifying talent circulation structure in Chinese academia