中国科技期刊研究 ›› 2019, Vol. 30 ›› Issue (8): 827-831.doi: 10.11946/cjstp.201903290206

• 质量建设 • 上一篇    下一篇

科技论文伪造数据的识别与防范

李侗桐1,)2),冯秋蕾1,)2),韩鸿宾1)()   

  1. 1) 北京大学医学部科学研究处,北京市海淀区学院路38号 100191
    2) 《中华医学科研管理杂志》编辑部,北京市海淀区学院路38号 100191
  • 收稿日期:2019-03-29 修回日期:2019-06-21 出版日期:2019-08-15 发布日期:2019-08-30
  • 通讯作者: 韩鸿宾 E-mail:kgzz@bjmu.edu.cn
  • 作者简介:李侗桐(ORCID:0000-0002-7488-7105),硕士,编辑,E-mail: litongtong@bjmu.edu.cn|冯秋蕾,硕士,编辑

Identification and prevention of data falsification in scientific articles

LI Tongtong1,)2),FENG Qiulei1,)2),HAN Hongbin1)()   

  1. 1) Department of Scientific Research,Peking University Health Science Center, 38 Xueyuan Road, Haidian District, Beijing 100191, China
    2) Editorial Office of Chinese Journal of Medical Research Management, 38 Xueyuan Road, Haidian District, Beijing 100191, China
  • Received:2019-03-29 Revised:2019-06-21 Online:2019-08-15 Published:2019-08-30
  • Contact: HAN Hongbin E-mail:kgzz@bjmu.edu.cn

摘要:

【目的】探讨科技论文伪造数据的识别和防范方法,以引起科技期刊编辑对隐匿性学术不端行为的关注。【方法】根据伪造数据的特点对其进行分类,梳理科技论文可能出现的典型伪造数据案例,并提出应对措施。【结果】常见的伪造数据类型有捏造数据、虚报样本量和篡改数据,编辑应从作者专业背景、论文方法描述、修改内容对比以及论证逻辑梳理等方面识别学术不端行为,科技期刊应提升编辑鉴别能力,加强作者科研诚信意识,完善管理惩戒制度,以防范论文数据造假。【结论】本研究可为编辑识别和防范科技论文伪造数据等学术不端行为提供借鉴和参考。

关键词: 科技论文, 伪造数据, 防范, 识别

Abstract:

[Purposes] This paper aims to explore the identification and prevention methods on data falsification, so as to cause the editors of scientific journals to pay attention to insidious academic misconduct. [Methods] According to the classification and characteristics of data falsification, we took the typical cases in scientific articles as examples, and put forward the countermeasures. [Findings] Three common types of data falsification including fabricated data, false report on sample size, and tampering data are settled, and identification methods are provided in terms of author's background analyses, research methods description, modified contents comparison, and logical combing. It is recommended that editorial discriminating ability, authors' sense of scientific integrity, and punishment mechanism should be improved from the perspective of scientific journals to prevent data falsification in scientific articles. [Conclusions] This study provides a reference for further editorial work on identifying and preventing academic misconduct of data falsification in scientific articles.

Key words: Scientific article, Data falsification, Prevention, Identification