From concept to measurement: operationalizing and normalizing Integrity Risk Indicators by SCImago (IRIS).

IF 9.6 Q1 ETHICS
Rodrigo Sánchez-Jiménez, Vicente P Guerrero-Bote, Gali Halevi, Félix De-Moya-Anegón, Daniel Gómez González
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引用次数: 0

Abstract

The Integrity Risk Indicators by SCImago (IRIS) framework, developed by the SCImago Research Group, addresses growing concerns about trust in science by shifting research assessment from traditional output and citation-based measures toward the evaluation of institutional exposure to research integrity risks. Rather than focusing on individual misconduct, IRIS recognizes the central role of institutional incentive systems, governance structures, and operational cultures in shaping research integrity. IRIS provides a constructive, data-informed model for identifying structural vulnerabilities associated with practices such as authorship and affiliation patterns, dissemination and citation dynamics, publication venue credibility, and the sustainability and transparency of publication practices. The indicators are derived from bibliometric and publication data and are intended as signals of potential risk, not as diagnoses or judgments. Applied to Higher Education Institutions included in the SCImago Institutions Rankings, IRIS enables meaningful comparison through z-score normalization, placing heterogeneous indicators on a common, interpretable scale centered on the global mean. The use of standardized scores enhances sensitivity to the magnitude of deviations, allowing IRIS to better function as a risk detection system, rather than a competitive ranking, and to support institutions in strengthening responsible and trustworthy research environments.

从概念到测量:通过SCImago (IRIS)实现完整性风险指标的操作和规范化。
由SCImago研究小组开发的SCImago诚信风险指标(IRIS)框架通过将研究评估从传统的基于产出和引用的措施转向评估机构面临的科研诚信风险,解决了人们对科学信任日益增长的担忧。IRIS不是关注个人的不当行为,而是认识到机构激励制度、治理结构和运营文化在塑造研究诚信方面的核心作用。IRIS提供了一个建设性的、数据知情的模型,用于识别与实践相关的结构性漏洞,如作者身份和隶属关系模式、传播和引用动态、出版场所可信度以及出版实践的可持续性和透明度。这些指标来自文献计量学和出版物数据,旨在作为潜在风险的信号,而不是作为诊断或判断。IRIS应用于SCImago机构排名中的高等教育机构,通过z-score标准化实现有意义的比较,将异质指标置于以全球平均值为中心的共同可解释的尺度上。标准化分数的使用提高了对偏差程度的敏感性,使IRIS能够更好地发挥风险检测系统的作用,而不是竞争性排名,并支持各机构加强负责任和值得信赖的研究环境。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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