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2016 | OriginalPaper | Buchkapitel

4. Prevalent Action-Guiding Models of Scientific Expertise in Policy

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Abstract

Science-policy models guide the practice of the Intergovernmental Panel on Climate Change (IPCC) and other science-policy institutions. Such science-policy models are primarily about the general competence, responsibility and legitimate role of scientific experts, policymakers and other players at the science-policy interface. The central question of Part II is how well they help tackle the key challenge at the science-policy interface, i.e. help comply with the four general norms for expertise in policy (Part I)? The results of the evaluation and refinement of the predominant science-policy models will both contribute to the envisaged framework for the IPCC assessments on a more general level, and serve as useful “lenses” for the more specific evaluation of the integrated economic assessments of the IPCC (Part III). This chapter introduces the decisionist, the technocratic, the pragmatic and the legitimisation models of the role of scientific expertise in policy; these four models are prevalent in practice. Section 4.1 explains core common characteristics of these prevalent models. The systematic analysis of the four models – particularly their philosophical assumptions on scientific knowledge – as potential tools to realise the general norms for expertise in policy follows in Sect. 4.2. Finally, Sect. 4.3 explains how the analysis and evaluation of these models can be used for the evaluation of the IPCC’s work.

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Fußnoten
1
This presupposes that the systematic reconstruction of existing viewpoints is kindly disposed towards these viewpoints; it should try to make the assumptions that are de facto held by science-policy players as consistent and plausible as possible, i.e.: to make them worthwhile discussing.
 
2
In this sense, science-policy models are loosely related to the hypothesis of a policy cycle (see Sect. 3.​1.​1 and Dunn 2012, Chap. 1). By (policy) “ends” I mean (policy) objectives, i.e., ends in the sense of ends-in-view, in contrast to “ends actually attained” (see Chap. 6). The term “policy objectives” can either refer to (1) general goals, ethical values, basic interests, priorities or fundamental constraints related to a particular framing (agenda) of the problem or risk assessments, such as “planetary boundaries” (Rockström et al. 2009); or (b) their translation into more specific, possibly subordinate, policy targets, such as specific climate change mitigation goals. Policy means can be understood as courses of action decided on by governments or governmental institutions that can include a variety of policy instruments from carbon taxation to education funding; these instruments are intended to result in specific measures (i.e., technologies, behaviour, etc.). Such policy options can be decided through legislative acts, executive orders or court decisions at different governance levels.
 
3
There are obviously also many other factors concerning the work of the IPCC and other science-policy institutions, such as personal or structural inertia and restrictions faced by attempts to reform structures of scientific policy advice (Kitcher 2011, p. 11), but also the individual rationalities of the players at the science-policy interface (Sect. 3.​1). Yet, the models of the science-policy interface – as “ideas” and partly action-guiding values, or “role models,” or “basic principles” – are effective as well. Even in the case that the underlying assumptions about policy processes or the quality of scientific knowledge production are flawed in these models, they can wield high influence on the actual behaviour of individual players at the science-policy interface, or on the institutional arrangements of assessment bodies.
 
4
See Chap. 1, footnote 2 for an explanation, and Chap. 5 for a differentiated discussion of the nature of value judgements.
 
5
The “choice of a given policy alternative symbolizes the victory of one segment of the community over another” (Dunn 1994, p. 55), rather than a victory of “reason,” “truth” or “the public good.”
 
6
For Weber, “value-free” simply denotes not directly evaluating something in ethical terms. Weber was, however, well aware that judgements in the social sciences are always related to non-ethical values and subjective world views (Weber 1949). See Chap. 5 for more details.
 
7
A widely cited proponent of the technocratic model is, for instance, Schelsky (1979).
 
8
Particularly in the 1960s, the decisionist model came under increasing attack for precisely this reason (Grunwald 2008, p. 11).
 
9
From the perspective of most proponents of the technocratic model, the methodology of natural science is the only reliable foundation of scientific knowledge. That is why they usually do not use the plural (“the sciences”), but rather talk about “science.”
 
10
See Chap. 5 for a discussion of this term and its implications.
 
11
Another (still widespread) variation is the so-called “Red Book model” of assessment-making developed by NRC (1983). Yet, this could be interpreted as a variation of the decisionist model.
 
12
The technocratic model is often related to an etatist view of democracy (Immergut 2011).
 
13
The existence of this “legitimisation” phenomenon in practice also suggests that scientific advice has a considerable impact on policy (otherwise, policymakers would not use the legitimisation model so often in the political arena), although not in a direct manner (see Sect. 3.​1).
 
14
Some of which were already described by other authors, e.g., Weimer and Vining (1992, p. 18) regarding the “issue advocate.”
 
15
This model ignores the value of scientific policy advice in general. Moreover, some also advocate for the above-mentioned “science-policy pessimism” – which is similar to the “pure scientist” model – because they do not believe (for empirical reasons) that science can have a significant impact on policy due to the given rationalities in the policy realm (compare Sect. 3.​1.​1), independently from the quality of the scientific advice as such.
 
16
In some passages, however, Pielke creates the impression that the “honest broker” focuses on “if-then” statements similar to a decisionist understanding of science-policy. This view is shared by Brown who argues (2008, p. 487), “Despite his repeated assertion that science and policy are ‘inextricably interconnected’ (p. 79), and despite his endorsement of constructivist research on the co-production of facts and values (p. 122), Pielke sometimes seems to want to insulate politics from science.”
 
17
E.g., Jasanoff (1990, p. 229), Pielke (2007, p. 34), Beck (2009, p. 191), Valente et al. (2015). Concerning scientific reports and assessments in climate and energy policy, there is a huge number of studies that can be interpreted in terms of the legitimisation model. Some of these reports advocate e.g. nuclear power, while others advocate renewable energy sources, while yet another group of studies argues that geo-engineering is essential. Sarewitz (2004) points out that such a technocratic legitimisation approach frequently triggers “counter-expertise.” This is possible due to the many uncertainties and value judgements involved in such studies (see Part III).
 
18
Compare the deeper and critical analysis of the science-policy models in Chaps. 5 and 6.
 
19
Source: http://​www.​clickgreen.​org.​uk/​opinion/​opinion/​122949-scientists-say-durban-deal-is-inadequate-and-call-for-raise-in-ambitions.​html, accessed 16 Mar 2015. As this document reveals, many share Pachauri’s view in that regard.
 
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Metadaten
Titel
Prevalent Action-Guiding Models of Scientific Expertise in Policy
verfasst von
Martin Kowarsch
Copyright-Jahr
2016
DOI
https://doi.org/10.1007/978-3-319-43281-6_4