Abstract

AbstractThis chapter conceptualizes the emergence of a techno-scientific field (TSF) as a multiscalar and progressive establishment of a new set of epistemic and social rules. Drawing on science and technology studies and field theories, we design an original conceptual framework that allows us to formulate three propositions to characterize the process of emergence of a TSF. We use the emergence of synthetic biology (Synbio) as a ‘laboratory’ to test this framework. Each proposition refers to a determinant dimension in the process of emergence—heterogeneity, hierarchy, and autonomy. First, we claim that heterogeneity (of disciplines, research questions, visions, social norms) is constitutive of the emergence of a new TSF. Second, the population of Synbio researchers is highly stratified; a core group of scientific entrepreneurs (incumbents and challengers) plays an active role in the process of emergence. Third, strategies for the control of external resources are crucial to the structuration of the field, which is mirrored by the prominent role of core-group members as boundary spanners. An original scientometric approach is used to create specific variables that allow us to investigate both network and field structural dynamics bridging qualitative and quantitative approaches.

Highlights

  • Use of the term synthetic biology in the scientific literature dates back to the early twentieth century, contemporary synthetic biology started to bloom around the turn of the new millennium and has been presented as novel—perhaps even revolutionary—and ‘cool’

  • In their review published in the 2016 edition of the Handbook of Science and Technology Studies, Ed Hackett and his colleagues point to the different reasons which might explain the emergence of a new scientific field: coherent networks that arise around potentially generative questions or phenomena; new research instrumentation which allows the knowledge field to be extended; original research ideas that capture the attention of influential groups; the promise of new uses for new scientific knowledge; and, the cumulative effect of these factors which often condition the institutionalisation of a new field (Hackett et al 2016, p. 740)

  • 7In the 1980s, bridging the qualitative and quantitative approaches was a core objective of Michel Callon, who developed scientometric analysis based on actor-network theory (ANT) to map the dynamics of science (Callon et al 1986). 8These are the Center for Integrative Synthetic Biology (Massachussetts Institute of Technology, USA), the Institute of Systems and Synthetic Biology (Genopole, France), and Toulouse White Biotechnology (TWB, France). 9Shapira et al (2017) observe that our search strategy is far more restrictive than that exploited by Hu and Rousseau (2015)

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Summary

Introduction

Use of the term synthetic biology in the scientific literature dates back to the early twentieth century, contemporary synthetic biology started to bloom around the turn of the new millennium and has been presented as novel—perhaps even revolutionary—and ‘cool’. Field theory allows analysis of emergence from the perspective of the production of knowledge and artefacts and of the emergence of a social order that involves a common understanding of what is at stake, the power relations and hierarchies, and the rules that govern interactions. Our objective is both methodological and theoretical. Scholars for whom the discipline constitutes a key form of the organisation of scientific production generally consider disciplines to be stable organisational and cognitive entities They are not much interested in studying their emergence. The final section of the chapter presents the results of our analysis of Synbio to illustrate the fecundity of new scientometric methods applied within an analytical frame which draws on both STS and field theory

Theoretical Framework—The Emergence of Technoscientific Fields Revisited
Emergence as a Multi-Scalar Process
Strategic Control of External Relations
Use of Advanced Scientometrics and Qualitative Methods
Delineation
Heterogeneity
Distribution of Scientific Capital
Hierarchy
Autonomy
Conclusion
Findings
London
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