Liberata -- Graph Scientometrics for a Share Based System of Academic Publishing

2026-05-03

AI Summary

This study addresses the limitations of traditional bibliometric systems, which rely on outdated assumptions of small-scale scholarly communities and struggle to fairly assess contributions or ensure quality control in high-output, large-scale research environments, while remaining vulnerable to strategic manipulation. To overcome these challenges, the authors propose a novel academic evaluation framework based on continuous contribution shares. This approach replaces discrete author ordering with tradable contribution shares, integrating weighted citations and an academic market mechanism to foster a dynamic, long-term-oriented assessment system. Innovatively, it employs a dual-graph structure—comprising a share graph and a citation graph—to model scholarly contribution as a quantifiable and tradable continuous variable, augmented by modular correction factors and an academic capital market model. The resulting academic capital metrics naturally extend across institutional, geographic, disciplinary, and temporal dimensions, effectively curbing credit inflation and incentivizing high-quality research with enduring impact.

Abstract

Contemporary scientometric indicators remain anchored in paradigms and axioms from when academic research was conducted in small scholarly communities. With the global proliferation of scientific research, academia is now organized in large communities with high rates of information incompleteness regarding work impact and individual contributions. This has significant implications for how research output is measured and quality controlled, especially as the rate of academic publishing continues to rise. Exploits of complex systems are typically found at discrete transition points where rules turn on or off, and academia is not immune to this pattern. Exploitative career boosting strategies are a growing problem, largely enabled by misaligned incentives and traditional metrics that force discretization of credit to authors and prior works despite their fundamentally continuous nature. This article introduces Liberata's scientometrics, a share based framework for academic publishing and quality control. In this system, authorship positions are replaced with contribution shares that sum to unity and encode both ordinality and relative contribution distances. These shares can be traded on Liberata's academic marketplaces for quality control services such as peer review and replication, rewarding contributors based on the long term success of the work. Citations are weighted to guard against frivolous referencing and credit inflation, and modular correction factors allow multiple measures of impact. Liberata's metrics are formalized through two fundamental graphs, Shares and References, from which the system constructs academic capital and derives scientometrics capturing impact, risk, collaboration, collusion, value of quality control, and diversification. These metrics represent academic contributions and extend naturally to institutions, regions, time periods, and research fields.

Problem

• scientometrics
• academic publishing
• research evaluation
• authorship attribution
• credit allocation

Innovation

• contribution shares
• academic marketplace
• weighted citations
• scientometric graphs
• modular correction factors