理论探讨

学科交叉研究的可持续发展识别 ——以应急管理领域为例

  • 范春竹 ,
  • 韩 毅
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  • 1.西南大学计算机与信息科学学院  2.西南大学商贸学院
范春竹,女,1998年生,西南大学计算机与信息科学学院硕士研究生。 韩 毅,男,1972年生,西南大学商贸学院教授,博士生导师。

网络出版日期: 2022-11-11

Identification of Sustainable Development in Interdisciplinary Research: Taking the Field of Emergency Management as an Example

  • Fan Chunzhu ,
  • Han Yi
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  • 1.College of Computer and Information Science,Southwest University  2.Business College of Southwest University

Online published: 2022-11-11

摘要

[目的/意义]学科交叉研究是当前解决复杂性问题的重要手段,其研究活动在未来是否具有良好的发展 潜力和态势更是科研人员选题的重要关注点,文章尝试探索学科交叉的可持续发展测度方法,以期为学科交叉研 究遴选提供必要的帮助。[方法/过程]以应急管理领域1992—2019年发表的中文期刊论文为例,从学科交叉度、 学术影响力、社会影响力三个方面,通过拟合的累积分布函数二阶求导得到的累积加速度来综合识别样本学科交 叉研究的可持续发展特征。[结果/结论]通过累积加速度变化能够识别出学科交叉研究的可持续发展情况,从学 科交叉度、学术影响力和社会影响力三个方面则能够更为全面地探索问题;历史数据的累积加速度分布函数单调 递增时学科交叉研究呈现可持续发展态势,表明该方法具有一定的可预测性。

本文引用格式

范春竹 , 韩 毅 . 学科交叉研究的可持续发展识别 ——以应急管理领域为例[J]. 情报资料工作, 2022 , 43(6) : 30 -37 . DOI: 10.12154/j.qbzlgz.2022.06.004

Abstract

[Purpose/significance] Interdisciplinary research is currently an important means to solve some complexity problems. Whether its research activities have good development potential and trend in the future is an important con? cern for researchers. This paper attempts to explore the sustainable development measurement method to interdisciplin? ary research, in order to provide the necessary help for the selection of interdisciplinary research. [Method/process] Taking Chinese periodical papers published in the field of emergency management from 1992 to 2019 as an example, this paper comprehensively identifies the sustainable development characteristics of interdisciplinary research from three aspects: interdisciplinarity, academic impact and social impact. And then fits the cumulative distribution func? tion, calculates the cumulative acceleration obtained by the second-order derivation. [Result/conclusion] The sustain? able development of interdisciplinary research can be identified by the change of cumulative acceleration index, and the problem can be explored more deeply from interdisciplinarity, academic impact and social impact. When the cumu? lative acceleration distribution of historical data increases monotonically, the research presents a sustainable develop? ment trend, which shows that the method is predictable to some extent.
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