The Gerontocratization of Science: How hypergrowth reshapes knowledge circulation

2024-10-01

AI Summary

This paper investigates how exponential growth in scientific literature induces “scientific aging”—a phenomenon characterized by declining proportions of high-impact papers, slowing turnover of canonical works, and diminished visibility for novel research. Method: The authors formally define and operationalize this concept, developing a generative citation model that integrates stochastic discovery, cumulative advantage, and文献 growth dynamics; they validate the model using large-scale empirical citation network analysis. Contribution/Results: Findings demonstrate that runaway literature expansion is an endogenous driver of academic impact rigidity: it markedly reinforces the long-term dominance of seminal papers while reducing the probability that new publications enter the high-impact tier. These results challenge the conventional assumption that increased output inherently fosters innovation. The study provides critical quantitative evidence to inform reforms in research evaluation, funding allocation, and knowledge dissemination mechanisms.

Technology Category

• Cognitive Modeling & Cognitive Systems: Computational Creativity
• Knowledge Representation and Reasoning: Computational Complexity of Reasoning
• Reasoning under Uncertainty: Other Foundations of Reasoning under Uncertainty

Application Category

• Web Mining and Content Analysis: Models for Web evolution
• Social Networks and Social Media: Computational social science
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Scientific literature has been growing exponentially for decades, with publications from the last twenty years now comprising 60% of all academic output. While the impact of information overload on news and social-media consumption is well-documented, its consequences on scientific progress remain understudied. Here, we investigate how this rapid expansion affects the circulation and exploitation of scientific ideas. Unlike other cultural domains, science is experiencing a decline in the proportion of highly influential papers and a slower turnover in its canons. This results in the disproportionate persistence of established works, a phenomenon we term the ``gerontocratization of science''. To test whether hypergrowth drives this trend, we develop a generative citation model that incorporates random discovery, cumulative advantage, and exponential growth of the scientific literature. Our findings reveal that as scientific output expands exponentially, gerontocratization emerges and intensifies, reducing the influence of new research. Recognizing and understanding this mechanism is crucial for developing targeted strategies to sustain intellectual dynamism and ensure a balanced and healthy renewal of scientific knowledge.

Problem

• Exponential growth of scientific literature
• Decline in influential new research
• Gerontocratization of scientific knowledge

Innovation

• Generative citation model
• Random discovery integration
• Exponential growth analysis