ЕКСПЕРТИЗА В НАУЦІ: КОГНІТИВІСТСЬКИЙ ТА МЕНЕДЖЕРАЛІСТСЬКИЙ ПІДХОДИ
Introduction. The advancement of scientific knowledge has traditionally been accompanied by rigorous procedures for professional evaluation, ensuring objectivity, logical consistency, evidentiary support, and validity. These procedures serve as fundamental mechanisms for the self-organization and se...
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| Datum: | 2025 |
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| Hauptverfasser: | , , |
| Format: | Artikel |
| Sprache: | English |
| Veröffentlicht: |
PH “Akademperiodyka”
2025
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| Schlagworte: | |
| Online Zugang: | https://scinn-eng.org.ua/ojs/index.php/ni/article/view/912 |
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| Назва журналу: | Science and Innovation |
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Science and Innovation| Zusammenfassung: | Introduction. The advancement of scientific knowledge has traditionally been accompanied by rigorous procedures for professional evaluation, ensuring objectivity, logical consistency, evidentiary support, and validity. These procedures serve as fundamental mechanisms for the self-organization and self-regulation of the scientific system. However, as science becomes increasingly integrated into market-driven processes, evaluation procedures have evolved into components of management technologies.Problem Statement. This shift has undermined the traditional notion of science as a self-organized, self-regulating system. Simultaneously, the proliferation of open science practices and the emergence of new evaluation requirements — driven by the advancement of artificial intelligence technologies — have reshaped the principles of scientific expertise, offering grounds for cautious optimism regarding the future of scientific progress based on self-organization.Purpose. This study aims to identify emerging trends in scientific expertise, focusing on the expansion of itsfunctions, methods, and forms.Materials and Methods. The study has employed comparative analysis, conceptualization and explication ofkey concepts, and problem-oriented analysis.Results. The characteristics of managerialist and cognitivist approaches to evaluation have been clarified. New trends in scientific expertise have been identified, particularly in relation to the spread of open science practices and the integration of artificial intelligence into evaluation processes. It has been substantiated that the shift in assessment priorities from a cognitive to a managerial approach poses risks to the self-organizing capacity ofscience. However, open science practices and evolving assessment criteria linked to artificial intelligence technologies have created opportunities to mitigate these risks.Conclusions. Contemporary trends in scientific evaluation should be grounded in the expansion of expertcompetencies and the cultivation of a multidimensional expert culture. This approach would facilitate polylogue,foster scholarly discussion, ensure the assessment of both actual and potential scientific outcomes, and promote anappropriate recognition of negative scientific results. |
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