workshop policy & science: who defines the problem?

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Dialogue with Policy. Martina Padmanabhan Universität Passau Chair of Comparative Development and Cultural Studies SEA. Workshop Policy & Science: Who defines the problem? 7 th of July 2014, Charles Darwin House, Central London. 1 . Science policy-interface: Science myth. - PowerPoint PPT Presentation

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WorkshopPolicy & Science: Who defines the problem?7th of July 2014, Charles Darwin House, Central London

Dialogue with Policy

Martina Padmanabhan

Universität PassauChair of Comparative Development and Cultural Studies SEA

1. Science policy-interface:Science myth

• Complex systems can be fully understood• Uncertainty is reducible• Simple cause-effect relationships can always be

established

2. Science policy-interface:Policy myth

• Social-ecological systems must be understood before deciding

• With enough knowledge these systems are controlable• A decision is the end of a linear process, neutrally

considering pros and cons

3. Science policy-interface:Science-policy myth

• Science and policy are two independent domains• Truth speaks to power• Forums, where reported results lead to policies based

on evidence

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Policy-science interfaces:…are the many ways in which scientists, policy makers and others link up to communicate, exchange ideas, and jointly develop knowledge to enrich policy and decisions-making processes and research.…are complex interaction and learning processes.

Science policy-interface1. Key feature: Goals

• Clarity of scope and transparency of vision

• Objectives• Drivers

• like mandates or • demand from policy or

supply by research

Science policy-interface2. Key feature: Structure

• Independence of the science-policy interface: control and biases

• Range of interest, expertise and openness

• Financial and human resources

Science policy-interface3. Key feature: Processes

• Trust building• Building capacities by

making scientists understand policy makers and vice versa

• Adaptability• Procedures to anticipate

developments• Continuity of iterative

process• Conflict management

Science policy-interface4. Key feature: Outputs

• Relevance of timely and accessible i.e. policy briefs

• Quality ensurance• Convey message across

different domains relevant for various audiences

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Science policy-interface5. Key feature: Outcomes

• Social learning and change of thinking

• Behavioural impacts• Policy impact• Issue impact

Attributes of sucessful interfaces

• To understand influence and impact• Evaluate scenarios• Draw lessons from past experiences• Explain assessments‘ influence

1. Credibility2. Relevance3. Legitimacy4. Interation

Achieving Credibility

• Credibility is the preceived quality, validity and scientific adequacy of the people, processes and knowledge exchanges at the interface

Interface as seen by others Role of strategic „champions“ and charismatic

„ambassadors“ Transparency and traceability

Enhancing Relevance

• Relevance is the perception of the usefulness of the knowledge brokered, how well it relates to the needs of policy and society and how responsive the interface process is to the changing needs

Continous policy support builds trust Communicating understandably at relevant events Using „translators“ and „knowledge brokers“

Building Legitimacy

• Legitimacy is the perceived fairness and balance of the interface process

Important when knowledge is contested and decisions produce losers and winners

Wide participation of different groups: Multi-stakeholder dialogue

Conflict management

Dynamic Iteration

• Iteration is the dynamic interaction between science and policy

Emphasis on added value of dynamic and repetitive feature of interfaces

Important to consider long-term develomentKnowledge accumulates to institutional memory

Pitfalls of science-policy interfaces

1. Unclear goals and functions of interfaces2. Power influences lead to conflicts3. Interaction with media perceived as risky4. Focus on key individuals risky5. Lack of resources: interface as marginal activity

What to do?

• Designing interface even before inception - conceptualising interface ex ante

• Monitoring interface work – reflect on learning process

• Improving communication - what role may art play in this?

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Changing the institutional landscapeDraw conclusions for research policy by: enabling a learning culture in research Co-design, co-creation, co-evaluation

Thank you for your kind attention!

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Sources

Information on research group BioDIVAhttp://www.uni-passau.de/en/biodiva/home/

A website on the Net-Map toolbox for influence mapping of social networks (as developed by Eva Schiffer) http://netmap.wordpress.com/

The Spiral project on ‘Interfacing Biodiversity and Policy’ http://www.spiral-project.eu/

Information on the Project PoNa Shaping Nature: Policy, Politics and Polity http://www.sozial-oekologische-forschung.org/en/1427.php 23

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