图书情报知识 ›› 2018, Vol. 0 ›› Issue (6): 37-49.doi: 10.13366/j.dik.2018.06.037

• 专题·跨学科研究模式与特征 • 上一篇    下一篇

我国人文社会科学间跨学科模式研究

吕冬晴,谢娟,成颖,柯青   

  • 出版日期:2018-11-10 发布日期:2018-11-10

Interdisciplinary Patterns of Humanities and Social Sciences in China

  • Online:2018-11-10 Published:2018-11-10

摘要:

为探索我国人文社会科学学科的总体跨学科模式及其演化规律,本文收集了CSSCI收录的1999—2009年23个学科的所有来源文献,及其参考文献与施引文献,采用RDI、SCI和CDI三个指标分别对观测学科的知识输入、知识内化和知识输出三个维度的跨学科性进行测度,通过聚类分析完成了跨学科模式的识别。研究表明,我国人文社会科学学科总体上表现为“内聚型”、“收敛型”、“平衡型”以及“开放型”四类跨学科模式;在历时分析中还出现了“偏倚型”和“发展型”两类特殊的跨学科模式;随时间推移,各学科的跨学科演化模式呈现出“低平模式”、“高平模式”、“剧烈波动”和“均衡波动”四类。作为跨学科模式的应用,论文扼要讨论了其对于学科建设的意义。

关键词: 跨学科研究, 跨学科模式, 跨学科演化模式, 人文社会科学, 聚类分析

Abstract:

In order to explore the interdisciplinary patterns and the evolution laws of humanities and social sciences in China, the bibliography of papers relating to twentythree disciplines between 1999 and 2009 were downloaded from Chinese Social Sciences Citation Index(CSSCI), including their references and citing articles.Reference Diversity Index(RDI), Selfcitation Index (SCI) and Citation Diversity Index(CDI) were used to measure the degree of interdisciplinarity from the perspectives of knowledge input, knowledge internalization and knowledge output respectively.The interdisciplinary patterns and its evolution laws were identified with Kmeans algorithm. It has been indicated that there are generally four types of interdisciplinary patterns, namely “cohesive pattern”, “convergent pattern”, “balanced pattern” and “open pattern”. Furthermore, two special interdisciplinary patterns which are “skew pattern” and “developmental pattern” have been captured in the analysis over years. Four types of evolution patterns, including “lowsteady mode”, “highsteady mode”, “drastically fluctuating” and “balanced fluctuating” have been discovered as the result of clustering analysis. As an application of interdisciplinary pattern research, this paper finally discussed the significance for discipline construction and development.

Key words: Interdisciplinary research, Interdisciplinary pattern, Interdisciplinary evolution pattern, Humanities and Social Sciences, Cluster analysis