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<p>The increasing reliance on quantitative research evaluation metrics has intensified concerns regarding their susceptibility to misuse, gaming, and misalignment with the broader principles of research integrity and responsible assessment. While traditional bibliometric indicators such as citation counts and journal-based metrics provide useful signals of scholarly influence, they often fail to adequately capture ethical, collaborative, and qualitative dimensions of academic work. In response, this paper proposes a conceptual framework for integrity-centered research evaluation through the introduction of the Composite Research Integrity Index (CRI) for individual researchers and the Institutional Integrity Index (III) for research organizations. The proposed framework integrates multiple dimensions related to publication ethics, citation quality, scholarly contribution, mentorship, visibility, and institutional practices, while emphasizing adaptability across disciplinary and organizational contexts. Rather than presenting universally fixed operational metrics, the study offers an exploratory and modular methodological formulation intended to illustrate how integrity-related dimensions may be incorporated into composite evaluation systems. To bridge conceptual design and practical applicability, the paper further discusses potential implementation architectures, including trusted third-party evaluation models, heterogeneous data integration, and AI-assisted analytical support operating within human-governed workflows. Illustrative case studies are presented to demonstrate the interpretive behavior of the proposed indices using realistic semi-synthetic profiles. The paper also critically discusses methodological limitations, infrastructural dependencies, governance considerations, and challenges associated with data quality, interoperability, and responsible use of artificial intelligence. Overall, the study contributes a conceptually grounded and forward-looking perspective on integrity-centered research assessment while outlining directions for future methodological refinement and empirical validation.</p>

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Beyond citation counts: integrity-centered metrics for ethical evaluation of researchers and institutions

  • 期刊论文

  • 发表日期：

    2026年6月29日

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  • Qutaiba I. Ali

摘要

The increasing reliance on quantitative research evaluation metrics has intensified concerns regarding their susceptibility to misuse, gaming, and misalignment with the broader principles of research integrity and responsible assessment. While traditional bibliometric indicators such as citation counts and journal-based metrics provide useful signals of scholarly influence, they often fail to adequately capture ethical, collaborative, and qualitative dimensions of academic work. In response, this paper proposes a conceptual framework for integrity-centered research evaluation through the introduction of the Composite Research Integrity Index (CRI) for individual researchers and the Institutional Integrity Index (III) for research organizations. The proposed framework integrates multiple dimensions related to publication ethics, citation quality, scholarly contribution, mentorship, visibility, and institutional practices, while emphasizing adaptability across disciplinary and organizational contexts. Rather than presenting universally fixed operational metrics, the study offers an exploratory and modular methodological formulation intended to illustrate how integrity-related dimensions may be incorporated into composite evaluation systems. To bridge conceptual design and practical applicability, the paper further discusses potential implementation architectures, including trusted third-party evaluation models, heterogeneous data integration, and AI-assisted analytical support operating within human-governed workflows. Illustrative case studies are presented to demonstrate the interpretive behavior of the proposed indices using realistic semi-synthetic profiles. The paper also critically discusses methodological limitations, infrastructural dependencies, governance considerations, and challenges associated with data quality, interoperability, and responsible use of artificial intelligence. Overall, the study contributes a conceptually grounded and forward-looking perspective on integrity-centered research assessment while outlining directions for future methodological refinement and empirical validation.