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Workshop Policy & Science: Who defines the problem? PowerPoint Presentation
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Workshop Policy & Science: Who defines the problem?

Workshop Policy & Science: Who defines the problem?

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Workshop Policy & Science: Who defines the problem?

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

  2. 1. Science policy-interface:Science myth • Complex systems can be fully understood • Uncertainty is reducible • Simple cause-effect relationships can always be established

  3. 2. Science policy-interface:Policy myth • Social-ecologicalsystems must beunderstoodbeforedeciding • Withenoughknowledgethesesystemsarecontrolable • A decisionisthe end of a linear process, neutrallyconsideringprosandcons

  4. 3. Science policy-interface:Science-policy myth • Science andpolicyaretwoindependentdomains • Truthspeaksto power • Forums, wherereportedresultsleadtopoliciesbased on evidence

  5. 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.

  6. Science policy-interface1. Key feature: Goals • Clarityofscopeandtransparencyofvision • Objectives • Drivers • like mandatesor • demandfrompolicyorsupplybyresearch

  7. Science policy-interface2. Key feature: Structure • Independence ofthescience-policyinterface: controlandbiases • Range ofinterest, expertiseandopenness • Financial and human resources

  8. Science policy-interface3. Key feature: Processes • Trust building • Building capacitiesbymakingscientistsunderstandpolicymakersandviceversa • Adaptability • Procedurestoanticipatedevelopments • Continuityof iterative process • Conflictmanagement

  9. Science policy-interface4. Key feature: Outputs • Relevanceoftimelyandaccessible i.e. policybriefs • Quality ensurance • Conveymessageacross different domainsrelevant forvariousaudiences

  10. Science policy-interface5. Key feature: Outcomes • Sociallearningandchangeofthinking • Behaviouralimpacts • Policyimpact • Issueimpact

  11. Attributes of sucessful interfaces • Tounderstandinfluenceandimpact • Evaluatescenarios • Draw lessonsfrompastexperiences • Explainassessments‘ influence • Credibility • Relevance • Legitimacy • Interation

  12. Achieving Credibility • Credibilityisthepreceivedquality, validityandscientificadequacyofthepeople, processesandknowledgeexchanges at theinterface • Interface asseenbyothers • Roleofstrategic „champions“ andcharismatic „ambassadors“ • Transparencyandtraceability

  13. Enhancing Relevance • Relevanceistheperceptionoftheusefulnessoftheknowledgebrokered, howwellitrelatestotheneedsofpolicyandsocietyandhowresponsivetheinterfaceprocessistothechangingneeds • Continouspolicysupportbuildstrust • Communicatingunderstandably at relevant events • Using „translators“ and „knowledgebrokers“

  14. Building Legitimacy • Legitimacyistheperceivedfairnessandbalanceoftheinterfaceprocess • Importantwhenknowledgeiscontestedanddecisionsproducelosersandwinners • Wide participationof different groups: Multi-stakeholderdialogue • Conflictmanagement

  15. Dynamic Iteration • Iterationisthedynamicinteractionbetweenscienceandpolicy • Emphasis on addedvalueofdynamicand repetitive featureofinterfaces • Importanttoconsiderlong-term develoment • Knowledge accumulatestoinstitutionalmemory

  16. Pitfalls of science-policy interfaces Uncleargoalsandfunctionsofinterfaces Power influencesleadtoconflicts Interaction withmediaperceivedasrisky Focus on keyindividualsrisky Lack ofresources: interfaceas marginal activity

  17. What to do? • Designinginterfaceevenbeforeinception - conceptualisinginterface ex ante • Monitoring interfacework – reflect on learningprocess • Improvingcommunication - whatrolemayartplay in this?

  18. Changing the institutional landscape • Draw conclusions for research policy by: • enabling a learning culture in research • Co-design, co-creation, co-evaluation

  19. Thankyouforyourkindattention!

  20. 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