信息资源管理学报 ›› 2026, Vol. 16 ›› Issue (4): 151-160.doi: 10.13365/j.jirm.2026.04.151

• 研究论文 • 上一篇    

同行评议是否会打压颠覆性创新成果——来自开放同行评议的新证据

王贤文 尹逸贤 耿屿   

  1. 大连理工大学公共管理学院WISE实验室,大连,116024
  • 出版日期:2026-07-26 发布日期:2026-09-21
  • 作者简介:王贤文(通讯作者),博士,教授,博士生导师,研究方向为科学学、科学计量学,Email: xianwenwang@dlut.edu.cn;尹逸贤,博士生,研究方向为科学计量学、科技政策;耿屿,博士,研究方向为科学计量学。

Does Peer Review Suppress Disruptive Work? New Evidence from Open Peer Review

Wang Xianwen Yin Yixian Geng Yu   

  1. WISE Lab, School of Public Administration and Policy, Dalian University of Technology, Dalian, 116024
  • Online:2026-07-26 Published:2026-09-21
  • About author:Wang Xianwen(corresponding author), Ph.D., professor, doctoral supervisor, research interests including science of science, scientometrics, Email: xianwenwang@dlut.edu.cn; Yin Yixian, Ph.D. candidate, research interests including scientometrics, science and technology policy; Geng Yu, Ph.D., research interests including scientometrics.

摘要: 同行评议是否打压颠覆性创新成果,是科学计量学与科技政策领域的重要议题。本研究以人工智能领域顶级会议ICLR的公开评审数据为样本,分析科学论文的颠覆性程度与其在同行评议中得分之间的关系,并进一步探讨颠覆性成果与“非共识性”评价之间的关联。结果显示,颠覆性与同行评审得分之间存在显著的正向关联,即颠覆性程度越高的科研成果,越容易获得同行的高度认可,表明同行评议体系并未打压颠覆性成果,同时,未发现高颠覆性论文伴随明显的“非共识性”。这表明在人工智能这一快速发展的前沿领域,开放同行评议制度能够有效识别具有颠覆性潜力的优秀成果。本研究为科技管理部门优化评审专家结构、鼓励原始创新,构建更加开放和包容的科研评价体系提供了理论依据与实证支持。

关键词: 颠覆性成果, 原始创新, 同行评议, 非共识, ICLR

Abstract: Whether peer review suppresses disruptive work is a crucial topic in the field of scientometrics and technology policy. Using publicly available review data from the International Conference on Learning Representations (ICLR), a top-tier conference in the field of artificial intelligence, this study analyzes the correlation between the disruptiveness of scientific papers and their scores in peer review. We further explore whether disruptive works are accompanied by significant dissensus. It finds a significant positive correlation between paper disruption and review scores, indicating that more disruptive work is more likely to receive high recognition from peers. This suggests that the peer review system does not suppress disruptive work. Furthermore, no obvious dissensus was found to be associated with highly disruptive papers. This indicates that in the rapidly advancing frontier fields of artificial intelligence, open peer review can effectively identify outstanding work with disruptive potential. This study provides theoretical basis and empirical support for science and technology management departments to optimize the structure of review panels, encourage original innovation, and build a more open and inclusive research evaluation system.

Key words: Disruptive work, Original innovation, Peer review, Dissensus, ICLR

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