The construction of expertise is a key topic within STS, as is disagreement amongst experts (Shapin 1994; Collins & Evans 2002; Jasanoff 2009; Collins et al. 2020). Yet, categorising expert knowledge remains a problem. Formulations in terms of fields, disciplines, or domains come from an outside, “meta” position that sits uneasily with STS’s insights on the co-construction of scientific facts and social authority.
STS itself has been described as such an interdisciplinary endeavor with methodologies and theoretical frameworks that can be applied to different domains (Jasanoff 2016). The past decade has seen efforts to develop new forms of “domain-general” expertise such as metascience and data science (Evans & Foster 2011; Ioannidis et al. 2015; Munafò et al. 2017; Strasser & Edwards 2017; Ribes et al. 2019). These have different motivations and intervene in specific fields in different ways—as interlocutors, partners, and, even, diagnosticians. Often, different forms of expertise establish distinct epistemic cultures in order to protect their autonomy and avoid the open conflicts that reveal rival epistemological commitments (Knorr Cetina 1999). However, interactions between domain-general and domain-specific forms of expertise have produced new conflicts (Leonelli 2016; Peterson & Panosfky 2020).
This raises challenging questions. Does the incursion of domain-general expertise represent a threat to the autonomy of disciplinary scientists? What would ‘good relations’ across this divide look like? How are domain-specific skills like embodied knowledge and practical judgment absorbed into domain-general systems meant to enumerate, evaluate, or automate scientific practice? How should these new “sciences of science” make STS scholars rethink their own expertise, motivations, and roles in discussions of policy?
We welcome papers on topics including the evaluation of science, data-driven science policy, data-centric approaches to scientific research, automation in science, as well as other papers looking at how scientific expertise is being turned on epistemic cultures.
REFERENCES
Evans, James A., and Jacob G. Foster. 2011. “Metaknowledge.” Science 331(6018):721–25. doi: 10.1126/science.1201765.
Ioannidis, John P. A., Daniele Fanelli, Debbie Drake Dunne, and Steven N. Goodman. 2015. “Meta-Research: Evaluation and Improvement of Research Methods and Practices.” PLOS Biology 13(10):e1002264. doi: 10.1371/journal.pbio.1002264.
Collins, Harry M., and Robert Evans. 2002. “The Third Wave of Science Studies Studies of Expertise and Experience.” Social Studies of Science 32(2):235–96.
Collins, Harry M., Robert Evans, Darrin Durant, and Martin Weinel. 2020. Experts and the Will of the People. Cham: Palgrave Macmillan.
Jasanoff, Sheila. 2009. The Fifth Branch: Science Advisers as Policymakers. Harvard University Press.
Jasanoff, Sheila. 2016. “The Floating Ampersand: STS 
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Knorr Cetina, Karin. 1999. Epistemic Cultures: How the Sciences Make Knowledge. Cambridge, MA: Harvard University Press.
Leonelli, Sabina. 2016. Data-Centric Biology: A Philosophical Study. University of Chicago Press.
Munafò, Marcus R., Brian A. Nosek, Dorothy V. M. Bishop, Katherine S. Button, Christopher D. Chambers, Nathalie Percie du Sert, Uri Simonsohn, Eric-Jan Wagenmakers, Jennifer J. Ware, and John P. A. Ioannidis. 2017. ‘A Manifesto for Reproducible Science’. Nature Human Behaviour 1(1):0021. doi: 10.1038/s41562-016-0021.
Peterson, David, and Aaron Panofsky. 2020. “Metascience as a Scientific Social Movement.” SocArXiv. August 4. doi:10.31235/osf.io/4dsqa.
Ribes, David, Andrew S. Hoffman, Steven C. Slota, and Geoffrey C. Bowker. 2019. “The Logic of Domains:” Social Studies of Science 49(3):281–309. doi: 10.1177/0306312719849709.
Shapin, Steven. 1994. A Social History of Truth: Civility and Science in Seventeenth-Century England. University of Chicago Press.
Strasser, Bruno J., and Paul N. Edwards. 2017. “Big Data Is the Answer … But What Is the Question?” Osiris 32(1):328–45. doi: 10.1086/694223.