Study on Peer Review and Multi-indicators Evaluation in Scientific and Technological Assessment

被引：4

作者：

Yu Liping ^{[1
]}

Pan Yuntao ^{[1
]}

Yang chun ^{[2
]}

Wu Yishan ^{[1
]}

机构：

[1] Inst Sci & Tech Informat China, Beijing 100038, Peoples R China

[2] Jiangsu Polytechn Univ, Coll Econom & Management, Jiangsu 213164, Peoples R China

来源：

KAM: 2008 INTERNATIONAL SYMPOSIUM ON KNOWLEDGE ACQUISITION AND MODELING, PROCEEDINGS | 2008年

基金：

中国国家自然科学基金;

关键词：

D O I：

10.1109/KAM.2008.39

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper analyzes the relation between peer review and multi-indicators evaluation for scientific and technical assessment. Based on the data of the 2007 Times Higher-QS world university rankings, we use two methods, multiple linear regression analysis and kappa agreement test, for analysis. The results show that the data abundance affects the agreement between peer review and multi-indicators evaluation. We conclude that comprehensive evaluation in combination with peer review is a better choice in lack of data. Regression goodness-of-fit can be used to assess data abundance. Peer review should be the basis for the choice of indicators and indicator weights. However multi-indicators evaluation is more stable and objective.

引用

页码：794 / 798

页数：5

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