| 融合研究范式的特征及测度研究 |
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| 引用本文： | 肖小溪,林德明,刘文斌.融合研究范式的特征及测度研究[J].科研管理,2022,43(12):190-197. |
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| 作者姓名： | 肖小溪 林德明 刘文斌 |
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| 作者单位： | 1.中国科学院科技战略咨询研究院，北京100190；
2. 大连理工大学科学学与科技管理研究所WISE 实验室，辽宁 大连116024；
3.北京师范大学-香港浸会大学联合国际学院工商管理学院，广东 珠海519087 |
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| 基金项目： | 国家自然科学基金：“‘融合式研究’的评价理论与实证研究——以生命与健康领域若干重大问题的研究为例”（71804176）；中国科学院科技战略咨询研究院青年基金项目：“‘融合科研’的评价理论与方法研究”（Y9X1761Q01）。 |
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| 摘 要： | 融合（convergence，或译为“会聚”）研究是一种基于多学科交叉来解决重大经济社会问题的科研范式，近年来成为主要国家高度关注的发展趋势。本文首先基于融合研究的本质探讨其在本体论、认识论和方法论上的基本特征，进而基于熵理论提出从方法论视角界定融合研究以及判断融合研究级段的指标——融合熵，并以脑科学研究为例进行该指标可行性和科学性的验证，为推动科技界形成对融合研究范式的更多共识以及相关政策制定奠定重要基础。
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| 关 键 词： | 融合研究 特征 测度 融合熵 |
| 收稿时间： | 2021-11-03 |
| 修稿时间： | 2022-04-15 |
A study of the characteristics and measurement of convergence research paradigms |
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| Xiao Xiaoxi,Lin Deming,Liu Wenbin.A study of the characteristics and measurement of convergence research paradigms[J].Science Research Management,2022,43(12):190-197. |
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| Authors: | Xiao Xiaoxi Lin Deming Liu Wenbin |
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| Institution: | 1. Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China;
2. WISE Lab of Institute of Science of Science and S&T Management, Dalian University of Technology, Dalian 116024, Liaoning, China;
3. School of Business Administration, Beijing Normal University-Hong Kong Baptist University United International College, Zhuhai 519087, Guangdong, China; |
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| Abstract: | Convergence research is a new research paradigm based on interdisciplinary approaches to solving major economic and social problems. In recent years, it has become a development trend that major countries pay great attention to. This paper first analyzes and reveals the characteristics of convergence research from the perspectives of ontology, epistemology and methodology, which illustrate the difference between the convergence research paradigm and the traditional research paradigm. Then this paper puts forward an entropy index, i.e., convergence entropy, to measure convergence research, and takes brain science research as an example to carry out empirical research with this index. There are mainly four theoretical results and conclusions from this paper. Firstly, convergence research is especially a holistic reflection on the ontology, epistemology and methodology of scientific research, instead of the paradigm shifting on the level of specific disciplines. Secondly, from the ontological point of view, the convergence research activities are mainly about natural ontology or social ontology, which means that the research problems or objects of convergence research are generally derived from the major challenges of nature and economic society, rather than simply deduced from the existing knowledge system. Thirdly, from the perspective of epistemology, convergence research is a typical constructivism, which not only requires knowledge construction at the individual level, but also emphasizes proactive, systematic and coordinated management and application of knowledge at the organizational and national levels. Fourthly, in terms of methodology, convergence research emphasizes wider openness and deeper integration. On the one hand, convergence research absorbs different disciplines according to the specific research problems, instead of the interaction of the same certain disciplines, which means that different research problems are solved by the convergence of different disciplines. In other words, convergence research involves a larger variety of disciplines at a deeper extent of interactions among these disciplines. On the other hand, convergence research will form a new research framework and research language through the "chemistry" interaction between disciplines, and eventually develop into convergence fields, rather than forming a new branch of disciplines. This paper also has important empirical results, which are mainly about the index of measuring convergence research. In detail, by using the index of convergence entropy to examine the development of brain science research from 1945 to 2020, it can be seen that global brain science research has experienced at least four development stages featured by their convergence entropy values during the 76 years. From 1945 to 1969 is the first development stage, showing a significant upward trend of convergence entropy. From 1970 to 1990 is the second development stage which means that global brain science research entered the plain period of multi-disciplinary integration, showing a relatively steady value of convergence entropy. From 1991 to 2011 is the third development stage, with the convergence entropy value of brain science research entering the second period of rapid increase, indicating that the multi-disciplinary convergence phenomenon in brain science research is more active than before. Since 2012, global brain science research has been in the fourth development stage, with the convergence entropy has been increasing rapidly again, after the brief plain period, which reflects that convergence research not only includes more and more disciplines in quantity, but also has a deeper degree of interdisciplinary integration. The above empirical results are highly consistent with the results of expert qualitative judgments made in 2011 in the USA, which concluded the three major changes in the field of life science research over the last 60 years. This empirical analysis indicates that the index of "convergence entropy" is scientific and feasible to quantitatively identify the convergence research and describe its convergence research stages.Finally, this study helps to promote the formation of consensus on the basic characteristics of convergence research in the science community, and removes cognitive barriers for policy making related to convergence research. It also lays a methodological foundation for the situation analysis and planning of convergence research. Of course, empirical studies on the index of "convergence entropy" in this paper are only conducted on the example of brain science. Whether the index needs to be revised when applied to other convergence fields needs to be furtherly studied, which is also important to promote the further development of convergence research theories and methods. |
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| Keywords: | convergence research characteristics measurement convergence entropy |
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