The landscape of scientific research communication is witnessing an unprecedented proliferation of research outputs. This increase in publications necessitates an evaluative framework that transcends traditional assessment metrics, such as the h-Index, which predominantly focuses on quantity and citation counts. In response to this need, we introduce the Author Identifier Metric Score (AIMS), a novel model designed to objectively quantify the productivity and impact of authors in scientific communication. AIMS presents a scoring system emphasizing the quality of research and mitigating the bias associated with first authorship. AIMS operates on a comprehensive algorithm combining fixed and variable scoring components to identify an author’s research calibre. The fixed score is calculated based on a credit distribution of authorship shares based on their contributions across various roles in the research and the nature of the publication medium. The variable score incorporates indicators of citation each paper has received over a period of time. The resultant AIMS score is a product of these components, offering a nuanced assessment of an author’s research credibility. AIMS is envisioned to serve multiple stakeholders within the academic ecosystem. For individual researchers, it provides a more accurate reflection of their scientific contributions, potentially influencing career progression and funding opportunities. Furthermore, the model holds potential for institutions, research evaluators and funding bodies for performance evaluation to discern research quality and allocate resources more judiciously. This paper delineates the theoretical underpinnings and practical implementation of AIMS, supported by case studies that exhibit its efficacy over conventional metrics. The discussion extends to the implications of AIMS on academic culture, addressing potential shifts towards quality-centric rather than quantity-centric research practices. This paper introduces a new model for a balanced scoring mechanism that rewards high-quality research endeavours with the possibility of fostering a more equitable and reflective scholarly assessment system.

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

From h-Index to AIMS: A Multi-dimensional Model for Comprehensive Research Impact Assessment

  • B. Sankar,
  • S. Rajath,
  • Mrityunjay Doddamani

摘要

The landscape of scientific research communication is witnessing an unprecedented proliferation of research outputs. This increase in publications necessitates an evaluative framework that transcends traditional assessment metrics, such as the h-Index, which predominantly focuses on quantity and citation counts. In response to this need, we introduce the Author Identifier Metric Score (AIMS), a novel model designed to objectively quantify the productivity and impact of authors in scientific communication. AIMS presents a scoring system emphasizing the quality of research and mitigating the bias associated with first authorship. AIMS operates on a comprehensive algorithm combining fixed and variable scoring components to identify an author’s research calibre. The fixed score is calculated based on a credit distribution of authorship shares based on their contributions across various roles in the research and the nature of the publication medium. The variable score incorporates indicators of citation each paper has received over a period of time. The resultant AIMS score is a product of these components, offering a nuanced assessment of an author’s research credibility. AIMS is envisioned to serve multiple stakeholders within the academic ecosystem. For individual researchers, it provides a more accurate reflection of their scientific contributions, potentially influencing career progression and funding opportunities. Furthermore, the model holds potential for institutions, research evaluators and funding bodies for performance evaluation to discern research quality and allocate resources more judiciously. This paper delineates the theoretical underpinnings and practical implementation of AIMS, supported by case studies that exhibit its efficacy over conventional metrics. The discussion extends to the implications of AIMS on academic culture, addressing potential shifts towards quality-centric rather than quantity-centric research practices. This paper introduces a new model for a balanced scoring mechanism that rewards high-quality research endeavours with the possibility of fostering a more equitable and reflective scholarly assessment system.