Drivers of collaboration to mitigate climate change: An illustration of Swiss climate policy over 15 years

Ingold, Karin; Fischer, Manuel

doi:10.1016/j.gloenvcha.2013.11.021

Cited by 142 publications

(134 citation statements)

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“…This result confirms that ideologies seem to matter more than power in conflictive policy subsystems (Ingold and Fischer 2014). It is further in line with former empirical analyses of the devil shift phenomenon, where expectations with respect to the power dimension could not be confirmed as clearly as those with respect to the "evilness" dimension (Sabatier et al 1987, 470).…”

Section: Discussionsupporting

confidence: 86%

Dealing with bad guys: actor- and process-level determinants of the “devil shift” in policy making

et al. 2015

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: Policy actors tend to misinterpret and distrust opponents in policy processes. This phenomenon, known as the "devil shift", consists of the following two dimensions: actors perceive opponents as more powerful and as more evil than they really are. Analysing nine policy processes in Switzerland, this article highlights the drivers of the devil shift at two levels. On the actor level, interest groups, political parties and powerful actors suffer more from the devil shift than state actors and powerless actors. On the process level, the devil shift is stronger in policy processes dealing with socio-economic issues as compared with other issues. Finally, and in line with previous studies, there is less empirical evidence of the power dimension of the devil shift phenomenon than of its evilness dimension.

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Section: Discussionsupporting

confidence: 86%

Dealing with bad guys: actor- and process-level determinants of the “devil shift” in policy making

et al. 2015

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“…We follow Ingold and Fischer (2014) with respect to model specification. See the supporting information for a detailed theoretical discussion.…”

Section: Exogenous Dependenciesmentioning

confidence: 99%

“…The directed outcome network reflects collaboration among four government agencies, five political parties, six scientific/research organizations, 11 organized interest groups (private-sector and business associations), and seven environmental nongovernmental organizations (NGOs ;Ingold 2008;Ingold and Fischer 2014).…”

mentioning

confidence: 99%

Navigating the Range of Statistical Tools for Inferential Network Analysis

Cranmer

Leifeld

McClurg³

et al. 2016

American J Political Sci

173

158

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“…In such a setting, scientists are expected to sit at the coalition's periphery (Ingold and Fischer, 2014). Cues for Type 2 reasoning need to come from the exogenous network environment, which will be introduced in the next section.…”

Section: How We Learnmentioning

confidence: 99%

Insights from ‘policy learning’ on how to enhance the use of evidence by policymakers

Witting

2017

Palgrave Commun

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This article uses the policy-oriented learning literature to provide practical insights on how to enhance the use of evidence by policymakers. After a short introduction to the field, this article presents four steps to understanding and responding to policy learning. First, all people interpret the world through the lens of their beliefs, and learn by combining heuristics and analytical processing. Second, people learn in different ways according to their roles. A novice would not be advised to learn about a specialist isue in the same way as a scientist. Instead, a modified communication strategy would be used to ensure understanding and uptake of evidence. Third, learning is a political process: we interact with our social environment and some actors-including entrepreneurs and brokers-influence the process more than others. Therefore, to encourage learning from scientific evidence we need to move beyond communication towards entrepreneurship and brokerage roles. In other words, policy-oriented learning is as much about interaction and leadership as information.

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Drivers of collaboration to mitigate climate change: An illustration of Swiss climate policy over 15 years

Cited by 142 publications

References 50 publications

Dealing with bad guys: actor- and process-level determinants of the “devil shift” in policy making

Dealing with bad guys: actor- and process-level determinants of the “devil shift” in policy making

Navigating the Range of Statistical Tools for Inferential Network Analysis

Insights from ‘policy learning’ on how to enhance the use of evidence by policymakers

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