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The role of science in NFP processes

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  1. The role of science in NFP processes Michael Pregernig

  2. Advance organiser • 2 ideal-types: • transfer model  transaction model • mode of interaction • integration of “values” and “facts” • type of output • type of knowledge use • Models of the science-policy interface • Design options for NFP processes and the role of science therein

  3. Science (facts) Politics (power,values) Truth knowledge closure policy choice Mode of interaction transfer model • “speaking truth to power” • spatial separation between a place of knowledge production and a place of knowledge use • “transport routes of information” as “one-way routes” transaction model • scientific know-how on its way into practical fields is subject to various transformations • science “diffuses” into society on different routes • network-model of knowledge diffusion

  4. Science (facts) Politics (power,values) Truth knowledge closure policy choice Type of output transfer model • simple transmission of ready-made scientific results • scientific questions are completely resolved, then finished product is handed over to policy-makers transaction model • scientific input to be understood as a social process • that evolves over time and involves long-term interactions between scientists, policy makers, interest groups, and citizens

  5. Science (facts) Politics (power,values) Truth knowledge closure policy choice Integrationof “values” and “facts” transfer model • facts can (and have to) be separated from values • those parts of decision-making requiring specialised knowledge should be depoliticised and left to experts transaction model • political counselling is a hybrid activity in which scientific expertise is accompanied by social and political judgements • defining and framing problems • selecting indicators • choosing criteria for analysis • making summaries • specifying recommendations

  6. Type of knowledge use • transfer model: instrumental use • policy makers consider the findings of a particular study … • in the context of a specific decision and … • adopt the course of action derived directly from the research • BUT: this kind of instrumental utilisation seems to be rare, particularly in complex problem settings • transaction model: conceptual use • research knowledge serves as a foundation for understanding • introduces new concepts and thus incrementally alters the language used in policy-circles • affects policies in diffuse ways • knowledge “creeps” into policy

  7. Type of knowledge use • symbolic/strategic use • expertise is simply an additional resource political actors can use in pursuing their interests • knowledge is nothing but a “hook” on which interests hang their case • roles of science in politics: • source of legitimacy, instrument of persuasion, mechanism for delaying/avoiding action, justification for unpopular policies etc. • question “Do ideas matter?” has mostly been ignored by mainstream political scientists • reflexive use • pay more attention to knowledge and ideas as explanatory factors in the creation of policies • diffusion of new ideas and information can lead to new patterns of behaviour • in problematic policy situations, actors rely on “frames”, in which values, social science models and interests are integrated

  8. Sources of information: • inferences from theoretical models • experiences from ongoing NFP processes • experiences from (U.S.) science-policy assessments Advance organiser • 2 ideal-types: • transfer model  transaction model • mode of interaction • integration of “values” and “facts” • type of output • type of knowledge use • Models of the science-policy interface • Design options for NFP processes and the role of science therein

  9. Policy relevance • questions important to the scientific community are not the same as those important to the policy community • “Begin and end with the policy problems, not the scientific problems.” • But: social systems of “science” and “politics” have different rationalities: • researchers are primarily driven by scientific curiosity • policy relevance is not a significant criterion • incentive structures in the academic world are hostile to praxis-oriented projects • scientists tend to turn praxis-oriented assessments into small disciplinary bits that can be easily published

  10. Policy relevance • different rationalities: (cont.) • science and politics have different time horizons • policy makers react to immediate concerns and agendas change rapidly • the pace of science is much slower and characterised by continuity • Design options • focus policy advice on identifiable user groups and political processes • keep science-policy advice processes focused on the policy-relevant problems throughout the process (e.g., through debriefings or through periodic progress reports)

  11. Issue-attention cycle • public issues go through an “issue-attention cycle“ • scientific inputs can come too late – when scientists answer salient questions too slowly to play a meaningful role in policy processes • scientific inputs can come too early – when assessments arrive before advocates in the issue domain have any interest in the information • Whom to address at what time? • pre-emergence phase  technical communities • post-emergence phase  political and management communities • Design options • generate policy questions interactively (scientists together with policy makers and stakeholders)

  12. Distance between science and politics In the context of knowledge use the cultural spaces of science and politics move close together, but: Only good fences keep politics and science good neighbours. • lose scientific autonomy and credibility • draw legitimation from the use of science in political decision making • lose perceived political utility and legitimation • neglect science for lack of credibility • legitimate their decisions byattaching to them the authorityof scientific expertise • neglect science for lack of salience • lose political autonomy

  13. Distance between science and politics Institutional forms: • Model A • provide for multipartite body that is capable, simultaneously, of negotiating differences over “facts” and values • problem: achieve harmonious political balance on the committee and maintain scientific credibility • Model B • divide “technical” issues from “political” issues and let “expert working groups” focus on the former and “policy group” on the latter • problem: linear, sequential structure of knowledge transfer

  14. Distance between science and politics Institutional forms: (cont.) • Model C • provide for two separate venues but give up rigid separation between science and politics • informally, experts appointed to an advisory body span a representative range of scientific and political positions • provide multiple opportunities for formal and informal interactions between different actors • relatively porous and flexible boundaries between the science and policy realms … without making the boundary between science and policy completely arbitrary or even non-existent • communicate a clear demarcation between science and policy to the outside but leave room to negotiate the location and meaning of the boundaries to the inside

  15. “Core” research vs. informed opinion • in science used in policy-making not only the context but also the content of research is distinct from that of “pure” research or “core” science • the questions scientists ask are not guided by a scientific paradigm alone, but by more instrumental considerations arising from the policy process • high degree of evaluation and meta-level analysis, rather than the elaboration of new facts • substantial extrapolation from existing research and the application of “informed opinion” of scientists

  16. Data vs. frameworks • traditional view: what policy makers want is just what researchers are best qualified to supply, namely data, findings, research conclusions • new insights: less tangible outcomes – including improved mental models of the problem – are at least as important as the more tangible outcomes – including policy recommendations and written reports • frameworks, more than data, are the key to successful science-policy consultation

  17. Single events vs. process oriented forms • repeated personal interactions over a longer period help … • to build up professional networks and to ensure respect and credibility • to build understanding by policy-makers of the problems at hand • policy actions are not “decided” in brisk and clear-cut style but decisions rather take shape gradually, they “accrete” • singular events (e.g., workshops, hearings) have a very limited chance to affect such processes • more process oriented forms of policy advice (e.g., series of related workshops, steady advisory bodies) are more effective

  18. Leaving a legacy • Institutionalisation • some of the most important outcomes associated with science-policy advice processes only accrue to the participants themselves • as these participants change jobs, the benefits begin to erode • to preserve the technical capacity and the professional relationships it may be appropriate to create new institutions or institutional practices(e.g., standing advisory committees, periodic workshops, electronic mail list servers) • Evaluation • lessons about how to conduct science-policy assessments should be identified and applied in future processes • each assessment process should conclude with an explicit evaluation of what worked and what did not • evaluation should provide the participants an opportunity to reflect on their experience and enable researchers to accumulate cases which can serve as the basis for serious comparative analysis

  19. Thank you for your attention! Michael Pregernig Institute of Forest Sector Policy and Economics University of Natural Resources and Applied Life Sciences (BOKU) Feistmantelstraße 4, A-1180 Vienna, AUSTRIA voice: ++43-(0)1-47654-4404  fax: ++43-(0)1-47654-4407  mail: michael.pregernig@boku.ac.at