Abstract

Building on group discussions and interviews with life science researchers in Austria, this paper analyses the narratives that researchers use in describing what they feel responsible for, with a particular focus on how they perceive the societal responsibilities of their research. Our analysis shows that the core narratives used by the life scientists participating in this study continue to be informed by the linear model of innovation. This makes it challenging for more complex innovation models [such as responsible research and innovation (RRI)] to gain ground in how researchers make sense of and conduct their research. Furthermore, the paper shows that the life scientists were not easily able to imagine specific practices that would address broader societal concerns and thus found it hard to integrate the latter into their core responsibilities. Linked to this, researchers saw institutional reward structures (e.g. evaluations, contractual commitments) as strongly focused on scientific excellence (“I am primarily paid for publishing…”). Thus, they saw reward structures as competing with—rather than incentivising—broader notions of societal responsibility. This narrative framing of societal responsibilities is indicative of a structural marginalisation of responsibility practices and explains the claim, made by many researchers in our sample, that they cannot afford to spend time on such practices. The paper thus concludes that the core ideas of RRI stand in tension with predominant narrative and institutional infrastructures that researchers draw on to attribute meaning to their research practices. This suggests that scientific institutions (like universities, professional communities or funding institutions) still have a core role to play in providing new and context-specific narratives as well as new forms of valuing responsibility practices.

Highlights

  • There is a long-standing debate about how far the engagement with the societal implications of emerging sciences and technologies has been able to change the cultures in which research is carried out

  • Instead of being a joint effort between social science and humanities (SSH) scholars and researchers in the sciences, there was a regularly a kind of division of labour: SSH scholars reflected on the possibilities for change, but there were no incentives for life scientists to really engage in changing the way they framed and conducted their research

  • The analyses of this paper show that researchers in the Austrian life sciences ascribe and assume responsibilities in reference to a strong culturally and institutionally anchored narrative infrastructure

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Summary

Introduction

There is a long-standing debate about how far the engagement with the societal implications of emerging sciences and technologies has been able to change the cultures in which research is carried out. Researching narratives makes it possible to understand important characteristics of the co-production of research and society, and how it is stabilised in specific current research environments This conceptual approach assumes that, despite situated differences in how life scientists assume and ascribe societal responsibilities, they share a set of narratives that allow them to make sense of this positioning work. In asking how researchers sketch their geography of responsibility, we understand researchers’ narrative infrastructure to be a language “through which meanings and values of academic knowledge/work and its relation to society can be articulated, circulated and exchanged across space and time” (Felt 2017) It serves as a frame of reference that allows researchers to make sense of their research processes (Felt 2017) and enables the communication of and reflection on complex and rather unfamiliar issues such as, in our case, the responsibilities between science and society. This serves as a basis to discuss how far material systems, administrative techniques and political rationalities stabilise certain notions of societal responsibility in research, while potentially marginalising others

Methods
Abbreviations
A Linear Model of Science–Society Relations
Findings
Conclusions
Full Text
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