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The rank boost by inconsistency in university rankings: Evidence from 14 rankings of Chinese universities
Author(s) -
Wen-Yu Chen,
Zhang-Qian Zhu,
Tao Jia
Publication year - 2021
Publication title -
quantitative science studies
Language(s) - English
Resource type - Journals
ISSN - 2641-3337
DOI - 10.1162/qss_a_00101
Subject(s) - rank (graph theory) , ranking (information retrieval) , similarity (geometry) , position (finance) , set (abstract data type) , government (linguistics) , political science , computer science , mathematics , information retrieval , business , combinatorics , artificial intelligence , image (mathematics) , programming language , linguistics , philosophy , finance
University ranking has become an important indicator for prospective students, job recruiters, and government administrators. The fact that a university rarely has the same position in different rankings motivates us to ask: To what extent could a university’s best rank deviate from its “true” position? Here we focus on 14 rankings of Chinese universities. We find that a university’s rank in different rankings is not consistent. However, the relative positions for a particular set of universities are more similar. The increased similarity is not distributed uniformly among all rankings. Instead, the 14 rankings demonstrate four clusters where rankings are more similar inside the cluster than outside. We find that a university’s best rank strongly correlates with its consensus rank, which is, on average, 38% higher (towards the top). Therefore, the best rank usually advertised by a university adequately reflects the collective opinion of experts. We can trust it, but with a discount. With the best rank and proportionality relationship, a university’s consensus rank can be estimated with reasonable accuracy. Our work not only reveals previously unknown patterns in university rankings but also introduces a set of tools that can be readily applied to future studies.

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