| 不同学科多属性评价横向比较研究——以数学、物理学、生物学期刊为例 |
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| 引用本文： | 俞立平,张全,刘爱军.不同学科多属性评价横向比较研究——以数学、物理学、生物学期刊为例[J].图书情报工作,2014,58(20):100-105. |
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| 作者姓名： | 俞立平 张全 刘爱军 |
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| 作者单位： | 1. 宁波大学商学院;
2. 沈阳工业大学信息科学与工程学院;
3. 南京农业大学经济管理学院 |
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| 基金项目： | 本文系浙江省自然科学基金项目“省际基础研究绩效的差距与形成机制研究”(项目编号:LY14G030005)和宁波大学人文社会科学培育项目“推进创新驱动发展的关键问题、影响机理与对策研究”(项目编号:XPYA13002)研究成果之一。 |
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| 摘 要： | 针对跨学科难以比较的问题,提出综合比较、结合数据分布、横向比较3个原则,并且以TOPSIS法为例,在对其进行优化的基础上,提出采用多属性评价结果的标准分进行跨学科比较的思想。以JCR 2012中的数学、物理学、生物学期刊为例进行实证分析,研究结果表明:基于标准分进行跨学科个体评价是可行的,甚至可以应用于不同评价指标与不同评价方法的横向比较;进行跨学科评价的样本数量不宜过少;不同学科的总体水平难以比较。
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| 关 键 词： | 学科 多属性评价 标准分 横向比较 |
| 收稿时间： | 2014-07-07 |
| 修稿时间： | 2014-09-01 |
Laterally Comparative Research on Multiple Attributes Evaluation for Different Disciplines: Taking Academic Periodicals as an Example |
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| Yu Liping,Zhang Quan,Liu Aijun.Laterally Comparative Research on Multiple Attributes Evaluation for Different Disciplines: Taking Academic Periodicals as an Example[J].Library and Information Service,2014,58(20):100-105. |
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| Authors: | Yu Liping Zhang Quan Liu Aijun |
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| Institution: | 1. Business School of Ningbo University, Ningbo 315211;
2. College of Information Science and Engineering, Shenyang University of Technology, Shenyang 110870;
3. School of Economics and Management, Nanjing Agricultural University, Nanjing 210095 |
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| Abstract: | It is difficult to compare cross-disciplinary research, three principles of integration comparison, Combined with data analysis and laterally comparative principles are provided. Taking TOPSIS method for example, on the basis of the optimization, a cross-disciplinary comparative idea for adopting standard score of multiple attributes evaluation outcomes is put forward. What's more, taking periodicals of CJR2012 math,physics, biology for examples, this paper conducts a positive analysis. The results show that cross-disciplinary evaluation based on standard score is feasible, and it can be even applied to laterally comparison for different evaluation indexes and different evaluation methods. The number of interdisciplinary evaluation sample size should not be too little, and it's hard to compare the overall level of different disciplines. |
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| Keywords: | discipline multiple attributes evaluation standard score laterally comparative |
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