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M. Pütz and R. Brassel
official experts who should debate the quality of scientific policy inputs, but indeed
all the actors affected by the issue and interested in contributing to a solution should
be included in the discussion (Funtowicz and Ravetz 1993: 752 et seq.; Ravetz
1999: 651). Gibbons et al. (1994: 1) also observed that the modes of knowledge
production had been changing. From their point of view, knowledge is no longer
solely produced disciplinarily and in a context of mainly scientific interests (Mode 1
knowledge production), but also transdisciplinarily and in “a context of application”
(Mode 2 knowledge production) (Gibbons et al. 1994: 3–5; Zscheischler et al. 2018).
However, there has been a shift not only in the way knowledge is produced and who is
involved in this process, but also in the way knowledge is exchanged (Bielak, Campbell, Pope, Schaefer, and Shaxson, 2008): referring to the findings of Funtowicz and
Ravetz (1993), Gibbons et al. (1994) and Pretty and Chambers (1993), Bielak et al.
(2008: 202 et seq.) asserted that
[i]t is no longer tenable to rely on the notion of a linear progression through an orderly
research process driven by scientists, to a dissemination phase driven by communication
specialists, to an adoption phase in which end users (whether in policy or management)
presumably apply research findings directly in their everyday activities. Rather, science
must be socially distributed, application-oriented, transdisciplinary, and subject to multiple
accountabilities. From a one-way linear process, science is evolving to a multi-party,
recursive dialogue.
The positivist perspective of “knowledge transfer”, where knowledge is understood as something that can simply be handed over to other individuals in a one-way
exchange process, has been complemented by other (more subjectivist) perspectives
(Rogga et al. 2014). Subjectivist perspectives take into account the idea that different
kinds of knowledge exist, which are individually and socially constructed (Fazey
et al. 2014: 206). Knowledge exchange arising from such a perspective “tend[s]
to result in knowledge exchange activities that encourage mutual learning through
multi-stakeholder interactions” (Fazey et al. 2014: 206), which is exactly what Bielak
et al. (2008: 202 et seq.) postulated. Therefore, today various definitions of knowledge exchange and a broad variety of different terms with diverging underlying
assumptions exist including “knowledge sharing, generation, coproduction, comanagement; transfer, brokerage, storage, exchange, transformation, mobilization, and
translation” (Fazey et al. 2013: 20; see also Mauser et al. 2013). In this article, we
understand knowledge exchange according to Fazey et al. (2013: 20) “as a process
of generating, sharing, and/or using knowledge through various methods appropriate
to the context, purpose, and participants involved.” However, knowledge exchange
does not always operate to the satisfaction of all the actors involved. Recently, various
scholars have begun to discuss the challenges of knowledge exchange at the intersection of science and public policy (which we refer throughout to as “science/policy
interfaces”) (Böcher and Krott 2014; Saarela and Söderman 2015; van Enst et al.
2014) and how they can be improved (Böcher and Krott 2014; Saarela and Söderman
2015). Others have focused on how knowledge exchange at science/policy interfaces
may be implemented most effectively (Reed et al. 2014).
In the following article, we investigate the different types of knowledge exchange
that actors in Switzerland have adopted at the intersection of science and public policy
M. Pütz and R. Brassel
official experts who should debate the quality of scientific policy inputs, but indeed
all the actors affected by the issue and interested in contributing to a solution should
be included in the discussion (Funtowicz and Ravetz 1993: 752 et seq.; Ravetz
1999: 651). Gibbons et al. (1994: 1) also observed that the modes of knowledge
production had been changing. From their point of view, knowledge is no longer
solely produced disciplinarily and in a context of mainly scientific interests (Mode 1
knowledge production), but also transdisciplinarily and in “a context of application”
(Mode 2 knowledge production) (Gibbons et al. 1994: 3–5; Zscheischler et al. 2018).
However, there has been a shift not only in the way knowledge is produced and who is
involved in this process, but also in the way knowledge is exchanged (Bielak, Campbell, Pope, Schaefer, and Shaxson, 2008): referring to the findings of Funtowicz and
Ravetz (1993), Gibbons et al. (1994) and Pretty and Chambers (1993), Bielak et al.
(2008: 202 et seq.) asserted that
[i]t is no longer tenable to rely on the notion of a linear progression through an orderly
research process driven by scientists, to a dissemination phase driven by communication
specialists, to an adoption phase in which end users (whether in policy or management)
presumably apply research findings directly in their everyday activities. Rather, science
must be socially distributed, application-oriented, transdisciplinary, and subject to multiple
accountabilities. From a one-way linear process, science is evolving to a multi-party,
recursive dialogue.
The positivist perspective of “knowledge transfer”, where knowledge is understood as something that can simply be handed over to other individuals in a one-way
exchange process, has been complemented by other (more subjectivist) perspectives
(Rogga et al. 2014). Subjectivist perspectives take into account the idea that different
kinds of knowledge exist, which are individually and socially constructed (Fazey
et al. 2014: 206). Knowledge exchange arising from such a perspective “tend[s]
to result in knowledge exchange activities that encourage mutual learning through
multi-stakeholder interactions” (Fazey et al. 2014: 206), which is exactly what Bielak
et al. (2008: 202 et seq.) postulated. Therefore, today various definitions of knowledge exchange and a broad variety of different terms with diverging underlying
assumptions exist including “knowledge sharing, generation, coproduction, comanagement; transfer, brokerage, storage, exchange, transformation, mobilization, and
translation” (Fazey et al. 2013: 20; see also Mauser et al. 2013). In this article, we
understand knowledge exchange according to Fazey et al. (2013: 20) “as a process
of generating, sharing, and/or using knowledge through various methods appropriate
to the context, purpose, and participants involved.” However, knowledge exchange
does not always operate to the satisfaction of all the actors involved. Recently, various
scholars have begun to discuss the challenges of knowledge exchange at the intersection of science and public policy (which we refer throughout to as “science/policy
interfaces”) (Böcher and Krott 2014; Saarela and Söderman 2015; van Enst et al.
2014) and how they can be improved (Böcher and Krott 2014; Saarela and Söderman
2015). Others have focused on how knowledge exchange at science/policy interfaces
may be implemented most effectively (Reed et al. 2014).
In the following article, we investigate the different types of knowledge exchange
that actors in Switzerland have adopted at the intersection of science and public policy