نقش نوآوری و فناوری در حکمرانی علم سنجی

Purpose: Traditional scientometric tools such as citation counts, h-index, and journal impact factors, and other quantitative indicators, although useful, face limitations in dealing with the complexities of contemporary knowledge networks and rapid scientific developments. These include the same names of authors, the instability of indicators, linguistic and regional biases, and the difficulty of identifying emerging trends. Given these challenges, the introduction of innovation and new technologies such as machine learning, data mining, natural language processing, dynamic network analysis, and artificial intelligence into the scientometric process is an inevitable necessity. These technologies can increase accuracy, transparency, fairness, and accountability in the scientific evaluation system. On the other hand, the concept of scientometric governance means a set of structures, rules, processes, and tools that determine "what and how to measure". Therefore, how technology and innovation affect this governance is a vital issue that has not yet been comprehensively examined. The present study aims to pursue several objectives. First, with the aim that science policy-making, decision-makers rely on scientometric data and indicators to allocate resources and design science development strategies. If these indicators are not sufficiently accurate or transparent, macro-scientific policies can lead to incorrect or unfair decisions. Second, from a theoretical perspective, it aims to combine new technologies with scientific governance theories to provide a basis for expanding the theoretical understanding of how to govern the science evaluation system. Third, with an applied aim, it aims to help promote the trust of researchers, reduce errors, and improve the efficiency of scientific evaluation systems by using technology in scientometric governance. In short, the aim of this study was to examine the role of innovation and technology in scientometric governance.
Methodology: The present study is quantitative and descriptive-analytical in nature, and the survey technique was used, and it is applied in terms of purpose. The statistical population of the present study was scientometric experts and data analysts, experts and managers of scientific evaluation units in universities, and representatives of scientific databases/reference libraries and scientometric service companies in Tehran. Given the limitations and possibilities of the researcher, the available sampling method was used, and given the lack of reliable statistics in the field of the research statistical population and the limitations and possibilities of the researcher, 100 people were selected as a sample using the available sampling method. The data collection method was fieldwork and the researcher entered the research field. The data collection tool was a researcher-made questionnaire based on English articles on the Likert scale (from completely agree to completely disagree) in this field. The data analysis method was used at two descriptive levels (demographic variables) and at the inferential level with simple regression (to test hypotheses). The software used was Spss.26.
Findings: The findings showed that: The use of new technologies in the scientometric process is positively related to increasing the accuracy of scientific evaluation, and the accuracy in the coefficient of determination shows that 73 percent of the changes in accuracy in scientific evaluation are explained by the use of new technologies. Also, technological innovation in scientometric structures promotes justice in scientific evaluation. (Accuracy in the coefficient of determination shows that 64 percent of the changes in justice in scientific evaluation are explained by technological innovation). In other results, it was found that: The use of new technologies increases transparency in scientometric governance, and the accuracy in the coefficient of determination shows that 70.2 percent of the changes in transparency in scientometric governance are explained by the use of new technologies. Finally, the precision in the coefficient of determination shows that 61.1% of the changes in responsiveness in scientometric governance are explained by the use of new technologies, meaning that the use of new technologies increases responsiveness in scientometric governance.
Conclusion: New technologies increase precision by providing tools to measure what was previously unmeasurable, allowing evaluators to go beyond the limitations of superficial quantitative measures and gain a deeper understanding of scientific value. Technological innovation moves towards a system of blind scientific evaluation of merit by replacing subjective judgments or limited criteria with objective, data-driven measures. New technologies transform scientometric governance from a centralized, black-box process to an open, verifiable, data-consensus-based system, which is the basis for trust and credibility in the entire scientific system. Technology transforms accountability from a moral obligation to a structural imperative, where every decision is subject to review and officials must justify not only the results but also the processes that led to those results. In fact, the use of new technologies improves scientometric governance indicators and the speed of assessments