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Short abstract:

By reconstructing the framework of structures and mechanisms, this paper aim to provide a lucid overview of current landscapes in STS, offering researchers directional guidance for venturing into this domain and furnish support for effectively integrating emerging technologies in exploring science.

Long abstract:

In recent years, researchers in the SoS have deployed Price's (1963) concept to build a complementary list of scientific mechanism theories and emerging metrics based on scientific properties, aiming to reveal unmeasurable scientific structures and mechanisms currently (Wu et al., 2022). However, this seemingly innovative classification overlooks the fundamental distinctions between the two core research objects in STS: knowledge content per se and the production and dissemination of knowledge within the academic collective. Moreover, due to the confusion of the concept of structure and mechanism, many theories and findings are misclassified. These misunderstandings may hinder researchers from more systematic and in-depth consideration of metrics while focusing excessively on identifying empirical characteristics of hidden mechanisms rather than analyzing their varying significance in specific contexts or their relationship with macro structures. Simultaneously, this approach may mislead research institutions, funding agencies, and policymakers to pursue metrics diversity without comprehensive understanding. To address these issues, our perspective piece adopts a sociological lens to reconstruct a structures and mechanisms framework that integrates theories, models, and metrics, reorganizing existing findings in STS based on research objects and basic units of analysis (images, arguments, articles/people, and fields). By employing the analytical paradigm of structures and mechanisms (Zhao, 2022), this study unveils the concealed connections and gaps among previous research, thereby opening the black box from academic collective to scientific knowledge systematically. We believed that better understanding of the underlying structure and dynamics of science also provides a basis for effective evaluation of outcomes and productive science-policy.