中国科技期刊研究 ›› 2025, Vol. 36 ›› Issue (8): 1045-1057. doi: 10.11946/cjstp.202504020314

• 数字出版 • 上一篇    下一篇

出版领域学术不端风险分级预警体系探索与构建

郭晓亮1),3)()(), 张璐2),3), 尹淑英3), 景勇3)()(), 耿文茹3)   

  1. 1) 沈阳工业大学文法学院,辽宁省沈阳市经济技术开发区沈辽西路111号 110870
    2) 沈阳工业大学管理学院,辽宁省沈阳市经济技术开发区沈辽西路111号 110870
    3) 沈阳工业大学学报编辑部,辽宁省沈阳市经济技术开发区沈辽西路111号 110870
  • 收稿日期:2025-04-02 修回日期:2025-07-22 出版日期:2025-08-25 发布日期:2025-09-08
  • 通讯作者: *景 勇(ORCID: 0000-0002-5682-184X),硕士,副编审,E-mail: 24303910@qq.com
  • 作者简介:
    郭晓亮(ORCID: 0000-0003-2160-1676),博士,编审,E-mail:
    张 璐,博士研究生,编辑
    尹淑英,博士研究生,编辑
    耿文茹,硕士,副研究员。
    作者贡献声明: 郭晓亮:确定选题及写作思路,设计核心框架并撰写、修订论文; 张 璐:牵头负责数据及资料分析,撰写论文; 尹淑英:参与资料分析,撰写论文; 景 勇:参与数据整理,撰写论文; 耿文茹:参与修订、审核论文。
  • 基金资助:
    辽宁省社会科学规划基金重点项目“我国学术不端的系统治理与联合预防”(L22AXW005)

Exploration and construction of graded risk early warning system of academic misconduct for publishing field

GUO Xiaoliang1),3)()(), ZHANG Lu2),3), YIN Shuying3), JING Yong3)()(), GENG Wenru3)   

  1. 1) School of Humanities and Law,Shenyang University of Technology,111 West Shenliao Road,Economic & Technological Development Zone,Shenyang 110870,China
    2) School of Management,Shenyang University of Technology,111 West Shenliao Road,Economic & Technological Development Zone,Shenyang 110870,China
    3) Editorial Department of Academic Journals,Shenyang University of Technology,111 West Shenliao Road,Economic & Technological Development Zone,Shenyang 110870,China
  • Received:2025-04-02 Revised:2025-07-22 Online:2025-08-25 Published:2025-09-08

摘要:

目的 为从根本上将学术不端阻遏在形成之前,基于数智技术和主体交联构建前置化、系统化、智能化的学术不端风险分级预警体系。 方法 利用访谈法收集学术研究者、出版单位、监管部门等对学术不端治理的认知与要求,通过网络检索、电话调查等了解学术不端预警实践进展,运用德尔菲法收集专家意见并识别学术不端预警关键因素,采取逻辑分析法构建学术不端风险分级预警体系并分析其实现机制。 结果 创新性设计学术不端风险分级预警体系,构造学术不端风险预警指数(RAM)度量学术不端可能性。基于数据采集、分析研判、即时预警3大子系统,通过跨平台嵌入式模块进行流程预警、负面预警、互动预警,面向学术研究各环节、学术出版全流程、学术生态多领域协同避免萌芽态学术不端行为。 结论 学术不端风险分级预警体系是将学术不端防范关口前移的开拓性研究与前瞻性探索,促进学术不端治理从事后惩戒向事前预防的根本转变,从而有效维护学术诚信,确保学术研究健康发展。

关键词: 学术诚信, 学术不端, 风险预警, 分级预警, 学术征信, 数据挖掘

Abstract:

Purposes In order to fundamentally prevent academic misconduct before it forms, a pre-positioned, systematic and intelligent graded risk early warning system of academic misconduct is constructed based on digital intelligence technology and subject cross-linking. Methods The cognitions and requirements of academic researchers, publishing institutions, regulatory authorities, etc. on academic misconduct governance are collected by applying interview method; the practical progress of early warning of academic misconduct is understood through online retrievals and telephone surveys, etc.; the key factors of early warning of academic misconduct are identified by applying Delphi method to collect expert opinions; and the graded risk early warning system of academic misconduct is constructed and the implementation mechanism is analyzed by applying logical analysis method. Findings The graded risk early warning system of academic misconduct is designed innovatively, and the early warning index of risk of academic misconduct (RAM) is constructed to measure the likelihood of academic misconduct. Based on three main subsystems of data collection, analysis and judgment, and real-time warning, the process warning, negative warning, and interactive warning can be achieved through cross-platform adaptive embedded modules. Hence, the budding academic misconduct activities can be avoided collaboratedly facing the various aspects of academic research, the entire process of academic publishing, and the multi field of academic ecosystem. Conclusions The graded risk early warning system of academic misconduct is a pioneering research and prospective exploration that shifts the prevention threshold forward of academic misconduct, which can promote the fundamental transformation of academic misconduct governance from post punishment to pre prevention, so as to effectively maintain academic integrity, and ensure the healthy development of academic research.

Key words: Academic integrity, Academic misconduct, Risk early warning, Graded early warning, Academic credit, Data mining