发表机构
Department of Information Management, Peking University（北京大学信息管理系）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究基于OpenAlex大规模数据，发现跨学科引用模式从无共同基础转向部分重叠，语义距离持续下降，表明科学知识重组趋于保守和去中心化。
AI 中文摘要
本研究考察了跨学科知识组合的主导模式如何随时间发生变化。它解决了现有研究的一个局限：现有研究记录了单个作品层面颠覆性的下降，但未揭示跨学科知识流动的机制本身是否已经发生转变。基于来自OpenAlex的5600万篇论文和8.16亿条引用（1960-2025年），本研究根据引用论文与被引用论文的子领域集合之间的关系，将跨学科引用分为五种类型，并引入了一种基于SPECTER-v2论文摘要嵌入的语义距离度量。随后，研究表明，跨学科引用已显著地从没有共同学科基础的配置转向基于部分重叠知识库的类型，这种重新定向进一步反映在引用与被引用领域之间平均语义距离的持续下降上。这一转变与网络中经纪位置的扩散以及对更早期文献的更大依赖同时发生，与一个在跨学科覆盖范围上变得更广泛、更去中心化的系统相一致。最后，本研究讨论了这些发现对科学政策以及跨学科资助机制设计的启示。
英文摘要
This study examines how the dominant mode of cross-disciplinary knowledge combination has changed over time. It addresses a limitation of existing studies that document declining disruptiveness at the level of individual works but do not reveal whether the mechanisms of cross-disciplinary knowledge flow have themselves shifted. Drawing on 56 million publications and 816 million citations from OpenAlex (1960-2025), the study classifies cross-disciplinary citations into five types based on the set relationship between the subfield portfolios of citing and cited publications and introduces a semantic-distance measure derived from SPECTER-v2 embeddings of publication abstracts. It subsequently demonstrates that cross-disciplinary citations have shifted markedly away from configurations with no shared disciplinary ground toward types built on partially overlapping knowledge bases, a reorientation further reflected in a steady decline in average semantic distance between citing and cited fields. This shift co-occurs with a diffusion of brokerage positions across the network and a greater reliance on older literature, consistent with a system that has become broader and more decentralized in its interdisciplinary reach. Finally, this study discusses the implications of these findings for science policy and for the design of cross-disciplinary funding mechanisms.
