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Network assortativity for a multidimensional evaluation of socio-economic territorial biases in university rankings
by
Monaco, Alfonso
, Bellantuono, Loredana
, Lo Sasso, Andrea
, Amoroso, Nicola
, Bellotti, Roberto
, Tangaro, Sabina
in
Academic Performance - statistics & numerical data
/ Bias
/ Bibliometrics
/ Biology and Life Sciences
/ Business metrics
/ Competitive advantage
/ Computer and Information Sciences
/ Decoupling
/ Earth Sciences
/ Economic conditions
/ Economics
/ Evaluation
/ Geography
/ Humans
/ Italy
/ Learning
/ Neurosciences
/ Performance evaluation
/ Phenomenology
/ Physical Sciences
/ Rankings
/ Ratings & rankings
/ Research and Analysis Methods
/ Social Sciences
/ Socioeconomic Factors
/ Socioeconomics
/ Universities - classification
/ Universities - economics
/ Universities - statistics & numerical data
/ Universities and colleges
2025
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Network assortativity for a multidimensional evaluation of socio-economic territorial biases in university rankings
by
Monaco, Alfonso
, Bellantuono, Loredana
, Lo Sasso, Andrea
, Amoroso, Nicola
, Bellotti, Roberto
, Tangaro, Sabina
in
Academic Performance - statistics & numerical data
/ Bias
/ Bibliometrics
/ Biology and Life Sciences
/ Business metrics
/ Competitive advantage
/ Computer and Information Sciences
/ Decoupling
/ Earth Sciences
/ Economic conditions
/ Economics
/ Evaluation
/ Geography
/ Humans
/ Italy
/ Learning
/ Neurosciences
/ Performance evaluation
/ Phenomenology
/ Physical Sciences
/ Rankings
/ Ratings & rankings
/ Research and Analysis Methods
/ Social Sciences
/ Socioeconomic Factors
/ Socioeconomics
/ Universities - classification
/ Universities - economics
/ Universities - statistics & numerical data
/ Universities and colleges
2025
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Network assortativity for a multidimensional evaluation of socio-economic territorial biases in university rankings
by
Monaco, Alfonso
, Bellantuono, Loredana
, Lo Sasso, Andrea
, Amoroso, Nicola
, Bellotti, Roberto
, Tangaro, Sabina
in
Academic Performance - statistics & numerical data
/ Bias
/ Bibliometrics
/ Biology and Life Sciences
/ Business metrics
/ Competitive advantage
/ Computer and Information Sciences
/ Decoupling
/ Earth Sciences
/ Economic conditions
/ Economics
/ Evaluation
/ Geography
/ Humans
/ Italy
/ Learning
/ Neurosciences
/ Performance evaluation
/ Phenomenology
/ Physical Sciences
/ Rankings
/ Ratings & rankings
/ Research and Analysis Methods
/ Social Sciences
/ Socioeconomic Factors
/ Socioeconomics
/ Universities - classification
/ Universities - economics
/ Universities - statistics & numerical data
/ Universities and colleges
2025
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Network assortativity for a multidimensional evaluation of socio-economic territorial biases in university rankings
Journal Article
Network assortativity for a multidimensional evaluation of socio-economic territorial biases in university rankings
2025
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Overview
University rankings are published on a regular basis and taken as a reference by a widespread audience of students, researchers, and companies. Nonetheless, rankings can be affected by socio-economic dragging effects, since they often fail to incorporate information on the variegated conditions in which scores are reached. This inability to capture structural inequalities can generate self-reinforcing awarding mechanisms, e.g. in performance-based funding distribution, that amplify existing gaps and prevent from recognizing achievements of universities in difficult or emerging contexts. In a previous study, we demonstrated the existence of a socio-economic territorial bias in general rankings, which rate the global performance of institutions. However, the interplay of the variety of territorial contexts and the different features of specific disciplines can give rise to more complex effects. In this work, we investigate the influence of the local socio-economic condition on the performance of universities in rankings, considering a multidimensional representation of the phenomenon, involving the dependence on subject, time, and type of ranking. Our findings show that bibliometric rankings are significantly more affected than reputational ones by socio-economic dragging, which strikingly emerges especially in the natural and life science areas. We conclude the analysis by decoupling territorial dragging effects from the achieved ranked scores. Universities that benefit the most from the mitigation of the socio-economic territorial bias are typically located in territories, mostly outside Western Europe and North America, hosting either a capital or other important cities.
Publisher
Public Library of Science,Public Library of Science (PLoS)
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