Public participation for sustainability and social learning: Concepts and lessons from three case studies in Europe

Ecological Economics 69 (2010) 1712–1722

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Ecological Economics j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / e c o l e c o n

Analysis

Public participation for sustainability and social learning: Concepts and lessons from three case studies in Europe Eneko Garmendia a,b,⁎, Sigrid Stagl c a b c

Institute for Environmental Sciences and Technologies (ICTA), Autonomous University of Barcelona, Spain Environmental Economics Unit, Institute for Public Economics, University of the Basque Country, Spain Department of Socio-Economics, WU Vienna, Vienna University of Economics and Business, Austria

a r t i c l e

i n f o

Article history: Received 5 February 2009 Received in revised form 30 March 2010 Accepted 30 March 2010 Available online 6 May 2010 Keywords: Social learning Participatory approaches Integrated assessment Complex adaptive systems Natural resource management Energy policy

a b s t r a c t Shaping change such that it avoids losing potentially useful options for future development is a challenging task in the face of complex, coevolving socio-ecological systems. Sustainability appraisal methods, which open up dialogue and options before closing down and making suggestions, pay attention to the inclusion of various and conflicting points of view and address uncertainty, are increasingly used in the science, environment and energy policy domains. The quality of the process is seen as key to high quality appraisal outcomes. Dimensions of quality include learning opportunities which are seen as ways for addressing complexity and uncertainty. Participatory sustainability appraisal methods intend to support social learning among participants. Despite high expectations, social learning processes in sustainability appraisals are poorly conceptualized and empirically understudied. This paper (1) briefly reviews theories of social learning; (2) develops a conceptual framework for the analysis; and (3) presents an empirical application of the framework by use of data obtained from three energy and natural resource management case studies around Europe. © 2010 Elsevier B.V. All rights reserved.

1. Introduction Mounting knowledge of what influences the changes of nature and societies has brought us the insight that in the end we will not know everything. We have to learn to live in a complex world with high uncertainties and an unclear future. How to make ‘good’ decisions under these circumstances? This is a key challenge for resource managers and policy makers. Advances in our understanding of how natural and social systems interact along spatial and temporal scales need to be substantiated by democratic mechanisms which can deal with inherent problems of continuous change, uncertainty and multiple legitimate perspectives of the systems. In environmental decision making therefore the focus has shifted away from the outcome to the process and from pure expert judgement to using society as extended peer community (Funtowicz and Ravetz, 1990; O'Connor et al., 1996). When facts are uncertain, values in dispute, stakes are high and decisions urgent, scientists can provide useful input only by interacting with the rest of society (Funtowicz and Ravetz, 1990, 1994, 1999; Kasemir et al., 2003; Gimarães-Pereira et al., 2006). Making decisions about complex socioecological issues is then a process, where the actors involved are continuously learning from each other and where social learning ⁎ Corresponding author. E48015 Bilbao, Spain. Tel.: +34 946017103; fax: +34 946017100. E-mail addresses: [email protected] (E. Garmendia), [email protected] (S. Stagl). 0921-8009/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.ecolecon.2010.03.027

becomes a key governance process (Board on Sustainable Development, National Research Council, 1999; Parson and Clark, 1995; The Social Learning Group, 2001; Folke et al., 2005; Pahl-Wostl et al., 2007b). Social learning is explicitly based on the idea that processes are more important than states (Pahl-Wostl, 2002) and is related to the concept of bounded rationality (Lee, 1993). The latter concept was originally developed by Herbert Simon (1976), who observed that human beings have a limited information-processing capability and in contrast to substantive rationality favoured in neoclassical economics, he argued in favour of an alternative form of rationality, called procedural rationality and which had been developed in psychology. Behaviour is then rational, if it is the outcome of appropriate deliberation and therefore rationality depends on the quality of the process that it generates.1 When dealing with complex issues and high uncertainty the search for optimal solutions (substantive rationality) is less useful than a focus on the quality of the decision process (procedural rationality), which includes that learning among the counterparts will become an essential part of the outcome (Froger and Munda, 1994; O'Connor et al., 1996). Deliberative approaches that enhance collective learning processes among a diverse group of social actors, with different types of knowledge and perspectives, are thus central in the creation of new responses to threats for socio-ecological systems. A new generation of integrated appraisal tools that combine deliberative approaches with 1 In contrast common behaviour is considered substantively rational “when it is appropriate to the achievement of given goals within the limits imposed by given conditions and constrains (Simon, 1976).

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multicriteria appraisals have been developed, to support decision making processes (De Marchi et al., 2000; Munda, 2004; Proctor, 2004; Gamboa, 2006; Gamboa and Munda, 2007; Proctor and Drechsler, 2006; Messner et al., 2006; Stagl, 2005, 2006, 2007a; Stirling, 2006; Hermans et al., 2007; Roca et al., 2008). Also monetary valuation methods, which are based on the idea of economic rationality, were recently combined with deliberative elements in their valuation processes. These new approaches include different forms of participation (e.g. citizen juries, deliberative workshops, surveys) in the valuation exercises to emphasize the relevance of preference construction and learning among the counterparts in the decision making process (Kenyon and Hanley, 2004; Spash, 2007; Álvarez-Farizo et al., 2007; Dolan et al., 2007; Stagl, 2007a;Spash, 2008; Álvarez-Farizo et al., 2009). In summary, public and stakeholder participation, which includes deliberation and inclusion (Bloomfield et al., 2001), can initiate social learning processes that go beyond individual and often predefined interests and/or values, and create opportunities for a shared understanding and joint action (Fiorino, 1990; Laird, 1993; Webler et al., 1995; Schusler et al., 2003; Brugnach et al., 2008). But what exactly do we mean by social learning? Which is the scope of such a process in the context of sustainability? And how successful are deliberative processes as part of sustainability appraisals in stimulating social learning? The paper is organized as follows: Section 2 explores the role of learning as a way to deal with complexity and uncertainty in the context of sustainability. Section 3 presents a framework for mapping social learning. Section 4 uses this framework to study social learning in three real case studies that combine participatory processes with integrated appraisal tools in the context of natural resource management and energy policy in Europe. Section 6 discusses the results and concludes. 2. Social Learning—Concepts, Complexity and Uncertainty Socio-ecological systems are both complex and evolving and their management is faced with uncertainty and surprise, making it necessary to abandon the expectation to find a global steady state. Instead, managing complex, coevolving socio-ecological systems for sustainability requires the ability to cope with, adapt to and shape change without losing promising options for future development. Learning is a key avenue for dealing with complexity and uncertainty. It is therefore not surprising that learning is a common feature of social theories that are dynamic. Despite the recent hype in the literature around social learning (Mostert et al., 2007) agreement on key aspects of the concept of social learning is still missing, which often leads to confusion which slows down adoption and effectiveness of the concept. In the past “[n] either philosophers who focus on epistemology, the logical underpinnings of how we know, nor sociologists who study the social processes underlying how science works give much thought to this critically important collective process of learning and understanding” (Norgaard, 2004: 238). We reviewed relevant parts of the literature in political science, sociology, economics, psychology and natural resource management and found that there is no common conceptual understanding of the term social learning. Many researchers label the phenomena they are examining as `social learning', but this does not necessarily indicate a common theoretical perspective, disciplinary heritage, or even language (Parson and Clark, 1995; Stagl, 2007b). Links between disciplines are limited to cross-referencing, while theory development around social learning takes a different direction within each field. The term social learning conceals a great diversity. One of the most cited definitions of social learning is from psychologist Albert Bandura (1977) who emphasizes that individuals learn by observing the behaviours of others in addition to directly experienced reinforcement. Under this view individuals have an

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intermediate degree of individual autonomy and are neither fully controlled by environmental forces nor completely free to become what they choose. This framework was complemented by Vygotsky (1978) who asserts the fundamental role of social interaction in the development of cognition. Individuals are the learners although the learning process takes place in social settings and is socially conditioned. For other authors, as we will see in the following paragraphs, social learning refers to learning by social aggregates and implies collective and collaborative learning (Finger and Verlaan, 1995). In organizational management Argyris and Schön (1978, 1996), focusing on complex and ill structured problems, proposed a theory of learning, called double-loop learning. In contrast to single looplearning, double-loop learning implies changes in the underlying values and assumptions. In the same field and in more recent years, several authors have emphasized the relevance of this type of learning as a way to adapt to a continuously changing and increasingly complex environment, through collaborative action and dialogue that rest in the reflection of preexisting values and assumptions (Isaacs, 1993; Schein, 1993; Kofman and Senge, 1993). These theories are closely related to the action oriented “communities of practice” proposed by Wenger (1998). Organizational learning theories are increasingly used also in ecological economics. Müller and Siebenhüner (2007) use them for analysing the impact of environmental policy instruments on learning processes towards corporate sustainability and Siebenhüner and Arnold (2007) investigate when and why companies pursue processes of learning and change to integrate sustainability. Siebenhüner (2008) combines principal– agent approaches and concepts from organizational theory to explain observed variance in organizational learning and change in eight international environmental organizations. In political science Heclo (1974), Sabatier (1988), Hall (1993a,b), and Jenkins-Smith (1988) consider policy making as a process of social learning in contrast to those theories of the state that base the foundation of policy change in power struggles. Most of them agree that social learning can be considered as a way of shifting dominant ideas and belief systems that drive policy making, but there is no consensus about the source of this change. While some relate social learning with the autonomy of the state others consider the influence of the social context central for the learning process. In economics, traditionally the concept of rationality has dominated for many decades and the conceptualization of decision making and learning has played a minor role. However, evolutionary economists have used the concept of learning early on, especially in relation to technological development (Dosi and Nelson, 1994; Dosi et al., 1996, 2001). From this perspective reality is often too complex and uncertain to be fully understood and learning is claimed to overcome knowledge and problem solving gaps (Dosi et al., 1996). Learning is here more than information acquisition; it is rather the development or change of the mental models of the world. In the tradition of pragmatic philosophy, the relation of complexity and social learning goes back to the seminal work of John Dewey.2 From his perspective democracy is undermined by the intimidating complexity of industrial societies. To overcome this democratic crisis and to move towards knowledgeable citizenry with a sense of community, he sees the need for a social learning process based in experimental politics. Scientists should abandon technocratic and dominant positions and act as teachers who facilitate citizens’ capacity to make sensible political judgments and identify social needs and troubles (Lee, 1993). Dewey had great influence on the North American tradition of adaptive management (Holling, 1978; Walters, 1986; Lee, 1993; Gunderson, 1999; Norton, 2005) and in more recent years social 2 For an extended review of Dewey's works see the thirty-seven volume set of The Collected Works of John Dewey edited by Jo Ann Boydston (1969–1991) and published as The Early Works (EW), The Middle Works (MW) and The Later Works (LW). Carbondale and Edwardsville: Southern Illinois University Press.

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learning also appears of central importance within the collaborative and adaptive management literature in the European context (PahlWostl, 2002, Pahl-Wostl and Hare, 2004; Reed et al., 2006 Pahl-Wostl et al., 2007a,b, 2008a,b; Mostert et al., 2007). Dewey's view of nature as a constructed cultural artifact have also influenced current discussions in environmental ethics, and in the field of environmental pragmatisms, in which science is perceived as a creative activity that is going beyond the search for an objective truth, learning is seen as a central process to overcome the current environmental crisis, reconstruct the problems at hand and shape new values in society (see Light and Katz, 1996). In Science and Technology Studies (STS) and Risk Analysis social learning is promoted as a way to deepen and expand the definition of risk, without eliminating conflict, ambiguity, or indeterminacy (Wynne, 1992a,b). Social learning implies the capacity to reframe a given problem considering broader cultural values and its political and cultural connotations (Stirling, 1999). Moreover, “to learn significant things, we must suspend some basic notions about our worlds and ourselves, we must reflect in our deep beliefs and mental models” (Kofman and Senge, 1993: 17). From this STS perspective a social learning process enriched by diverse types of knowledge could enable an interactive process that is conscious of the consequences of uncertainty and complexity inherent to technological development allowing a new vision of knowledge system as an open and diverse system (Tàbara et al., 2005). Uncertainty, or more broadly indeterminacy, inhibits the creation of knowledge about consequences and thus causes difficulties for the use of science in the transition to sustainability. Complexity of social actions and the multitude of potential interventions with its infinite outcomes prevent any reliable prediction of the connections between individual choices and observed outcomes (Kauffman, 1993; Holland et al., 1996; Capra, 1996). Therefore in the face of the following system properties: bounded rationality, limited certainty, limited predictability, indeterminate causality, and evolutionary change an adaptive approach is preferable, where the actors go through a learning process that allow them to modify decision rules and mental models of the real world (Hjorth and Bagehri, 2006). Acknowledging the limits of knowledge creation while needing to make decisions, leads to a reliance on critical reflexive processes. As such social learning could play an important role, not just as a way to find new facts and a better understanding of relations and impacts but as a way to shape values and reflect on the assumptions and limitations behind our knowledge. Hence, social learning is based on the capacity to question the assumptions that underlie one's actions, values, and claims to knowledge (Brookfield, 1987; Flood, 1990; Pahl-Wostl, 2002). In contrast to the mere acquisition of factual knowledge, here we are closer to the state defined by Pablo Freire (1970) as “transitive critical consciousness” in which new values as critic, participation, democracy and freedom emerge. Taking these issues seriously requires adopting a precautionary approach which acknowledges the limits to our knowledge.3 In this sense “social learning must be conceived as more than just cognitive learning. Learning together to manage together has also to do with changes in attitudes, beliefs, skills, capacities, and actions in and among the counterparts” (HarmoniCOP, 2003:8). It has a cognitive but also a moral or normative part (Argyris and Schön, 1978; Webler et al., 1995). In summary, learning has become an important element of management, if the situation is characterized by incomplete knowledge, presence of novelty or surprises and qualitative changes that can lead to irreversibility (Hodgson, 2002; Gunderson and Holling, 2002). Learning

3 The precautionary approach involves in this context “much more than simply shifting the threshold of proof to a different place in the same available body of knowledge. The different social premises which shift implies also open up the possible reshaping of the natural categories and classifications on which that scientific knowledge is constructed” (Wynne, 1992b: 112).

also appears of central importance for socio-ecological systems to build resilience, the capacity to buffer perturbations (Folke et al., 2002; Rammel et al., 2007). More broadly, social learning is now regarded as a key element of the process to sustainability (Lee, 1993; Parson and Clark, 1995; Dryzek, 1997; Röling and Wagemakers, 1998; Stagl, 2007b; The Social Learning Group, 2001; Tàbara, 2003; Scott and Gough, 2003; Siebenhüner, 2004; Tàbara and Pahl-Wostl, 2007; Luks and Siebenhüner, 2007; Pahl-Wostl et al., 2007a, 2008a,b; Antunes et al., 2009) and it has been proposed as a process to overcome the difficulties derived from complexity, uncertainty and conflict ridden issues in the decision making processes related to natural resource management (Lee, 1993; Dryzek, 1997; Röling and Wagemakers, 1998). While the social learning literature tends to be quite heterogeneous, there are some remarkable commonalities; for example, the recognition of a process that is going beyond the acquisition of mere factual knowledge and the need to look beyond individual actors. However, as mentioned above, the lack of coherence among the different theories poses a great challenge for advancing the understanding of social learning processes. The following section highlights the elements of social learning that are particularly important in the context of sustainability and complex evolving systems. 3. Social Learning Dimensions: A Common Framework for Mapping Social Learning in the Context of Sustainability After presenting some links between sustainability and social learning and establishing that social learning processes go beyond cognitive learning, we pursue here the question of what we can learn, as suggested by Parson and Clark (1995). With this aim we systematically describe those elements of social learning that we consider as relevant for the transition to sustainability. Before doing so, we want to clarify our normative stance. While learning is a process which could go in any direction, social learning in the context of sustainable development has a normative dimension. Whereas unavoidable, we think that it is important to make this transparent, and to ensure that this is adequately reflected in the workshop design. Participatory processes should be designed such that they offer all participants the opportunity to learn. Despite this normative element, the design fosters open deliberation and exchange leading to perceptions change in any direction or not all. The processes during the workshops are not geared to convert or pressurise participants in any way. Hence, the participatory workshops have a normative basis, but are no persuasion tools. To structure our work we start out by following the structure proposed by Argyris and Schön (1978, 1996) in which they distinguish the above mentioned two types of learning and then add new components, borrowing insights from the literature on complex adaptive systems and post-normal science. The simplest mode of learning has to do with the acquisition of new cognitive knowledge. This category has been defined by Argyris and Schön (1978, 1996) as single loop or instrumental learning and refers to changes in strategies of action or assumptions underlying strategies in ways that leave the values of theory of action unchanged. A similar learning process is also defined by Webler et al. (1995) as cognitive enhancement. Kaiser and Fuhrer's (2003: 600–603) typology of cognitive knowledge is particularly useful here: (1) Declarative knowledge: usually contains answers to the question of how systems work (Schahn, 1996); it gives insights into the state of the problem. (2) Procedural knowledge: refers to behavioural options and possible courses of action (Ernst, 1994); it is about learning how to achieve a particular goal. (3) Effectiveness knowledge: contains (procedural) knowledge about the relative effectiveness of different behaviours to reach a certain outcome.

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Hypothesis 1. There is a change in knowledge within an existing frame of reference,4 which merely involves the adoption of new facts. This knowledge can be distinguished in: declarative knowledge, procedural knowledge and effectiveness knowledge. The second category of social learning comes from moral development, which highlights how individuals come to be able to make judgments about right and wrong (Kurtines and Gewirtz, 1987) and has been re-defined adapting Webler et al. (1995) as mutual understanding. This type of learning is closely related to second-loop learning defined by Argyris and Schön (1978, 1996) in which there is a change in the underlying values and assumption. Following Webler et al. (1995) authors have included in this dimension changes in attitudes, beliefs, skills, actions in and among the counterparts as essential elements of such a process (HarmoniCOP, 2003; Siebenhüner, 2004). In the context of sustainability, this type of learning reflects a capacity to scale the issues up from the individual and particular level to a more collective level and wider context, and to consider the silent voices (including future generations, non-human species and other unrepresented groups). It also implies a shift in the behavioural mode, from learning logical and empirical facts toward normative and affective values. It would then be acknowledged that the environment is characterized as a place of conflict between multiple legitimate values and interests and groups that represent them (Martinez-Alier et al., 1998); from this recognition a sense of mutual understanding, justice and respect could emerge. “[I]t is in the process of learning about the viewpoints of the others that stakeholders can learn to expand their own frames and see how their particular concerns and issues affect, and are affected by, the larger whole of which they are part” (Tippett et al., 2005: 292). We can identify three aspects of learning: • Learning about underlying reasons for behaviour; • Reflecting about and acquiring knowledge about other people's and groups’ interests and values; • Developing a sense of solidarity with a group (human and nonhuman, future generations), possibly adoption of collective interests as one's own. Hypothesis 2. There is a change in the appraisal of facts on the basis of modified values and assumptions and an increasing understanding of others perceptions and needs.5 To test this hypothesis, we identified three subhypotheses. Hypothesis 2.1. The participants learn how to (re)structure the problem at hand (framing or reframing) and change their perception of the problem. Hypothesis 2.2. There is an increased understanding of the other participants' viewpoints that results in a (positive) change in attitudes towards them. Hypothesis 2.3. Participants refine their knowledge about societal needs, expanding their views from the individual to the collective and considering other collectives like future generations or non-human species. Taking into account the concepts reviewed elsewhere (HarmoniCOP, 2003; Stagl, 2003) and the characteristics of complex evolving systems, we suggest including another category within social learning for sustainability. Transitions to sustainability evolve as part of fundamental 4

Frame of reference here refers to the underlying values and assumption. This also includes acknowledging non represented collectives like future generations and non-human species. 5

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change in the way people think about the complex systems upon which they depend (Folke et al., 2002). We define this category of social learning as learning how to deal with complex and uncertain systems. Transitions to sustainability will require a deep change in our understanding of the systems. This change can be illustrated by what Kofman and Senge (1993) called a “new Galilean Shift”, where we move from the primacy of pieces to the primacy of the whole, from absolute truths to coherent interpretations, from self to community, from problem solving to creating. In this type of learning, the subject becomes conscious and gains an imaginative and thus potentially also a practical mastery of whole systems of activity. This implies becoming conscious of the complexity and uncertainties of the issue at hand. “The acquisition of new knowledge, even desirable, seems insufficient to deal with contemporary issues. What is more urgently needed to get out of the past trends is a change in our values, in our perceptions of complexities and uncertainties. Adaptive learning and adjustment, guided by a much wider range of human experience and understanding than disciplinary science, are also necessary” (Kay et al., 1999: 721–742). Here we can identify four aspects of learning: • practicing holistic or integrative thinking which implies learning about complexity and uncertainties; • learning how to deal with conflict ridden situations, including conflict-solving skills and cooperation; • acquiring the capacity to realize more and better joint interactions at different levels, through new communities of practice (Wenger, 1998); • learning about the steps that can be taken for institutional change and joint action. Hypothesis 3. Participants refine their views about the complexities and uncertainties in the relevant systems. Hypothesis 4. Participants find ways for institutional change and joint action that open up the possibility to collaborate with others individuals. This also implies dealing with conflict riding issues in a constructive way, and being able to apply a similar approach of participation and integrative thinking in a different setting. Finally, as a crosscutting category or dimension to the previous ones, we include scale. The elements of social learning mentioned above can be placed at different levels: from the individual to the societal level, from the local to the global, from the short term to the very long term. In our understanding learning at a range of levels and between levels would be needed for shaping more sustainable pathways. Therefore we include the scale issue at a meta-level, as a component that should be considered in all categories of learning. Complex systems can only be understood from a hierarchical perspective. Each system is a subsystem of a bigger system, which in turn is part of a wider environment and where everything is connected (at least weakly) to everything else (Kay and Schneider, 1994). This also implies that different people looking at the same system, its elements and connections are going to define and perceive the system differently, unless they agree on the inevitably subjective criteria for deciding on scale, extent and hierarchy (Kay and Schneider, 1994). In other words the existence of different levels and scales at which a hierarchical system can be analyzed implies the unavoidable existence of non-equivalent descriptions of the system (Giampietro, 1994; Giampietro and Mayumi, 2000). In this sense learning about complex evolving systems must happen on various levels, e.g. the individual, group, organizational and institutional levels. These categories of social learning can be organized in three dimensions, according to the scale of the process; the system perception and the behavioural mode (see Fig. 1). As we move on the behavioural axis in Fig. 1 from left to right we move from the simplest form of learning, the acquisition of new facts,

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Fig. 1. Three dimensions of social learning.

to changes in framing or moral development. On the scale axis from bottom to top, the scope of learning shifts from the individual level to the institutional or structural level. In the systems perception axis, from right to left there is a change in a system's perception that implies a transition from a simple predictive and often command and control focused perspective to one that acknowledges the complex and uncertain properties of the surrounding coevolving systems. Social learning for sustainability requires moving from the small inner cube to the bigger outer cube. Social learning includes the elements of the inner cube, but by themselves they would be insufficient. Social learning also requires the outer elements of the cube, notably reframing, institutions and complex adaptive systems perspective. Social learning could therefore be defined as a learning process that happens among different elements and at different levels; it is going beyond the acquisition of new factual knowledge by individuals and includes changes in the frames of reference—assumptions and values— while creating capacity for dealing with conflict ridden issues and for finding ways for joint action. It also implies gaining capacity for systems thinking, notably about complexities and uncertainties, and perceiving oneself as part of a whole, notably recognizing future generations and non-human species. This requires deliberation among relevant social actors. Opportunities for social learning make the appraisal process more interesting and worthwhile for actors to participate and social learning happening is an important outcome of participatory processes. The claim that participatory processes are capable of fostering social learning processes in the context of sustainability needs empirical testing. While recently several empirical studies about social learning have been completed (Siebenhüner, 2002a,b; Schusler et al., 2003; Van den Kerkhof, 2004; Siebenhüner, 2004; Darby, 2006; Stagl, 2006; Mostert et al., 2007; Borowski et al., 2008) further empirical evidence is needed to develop a robust understanding of social learning processes. By using data from three own case studies in Europe we try to bridge this gap by exploring four hypotheses about social learning with real world data. 4. Case Studies In these case studies multicriteria assessment was combined with participatory approaches in relation to: (1) sustainable energy systems in Austria; (2) energy transition in Southeast England; and (3) sustainable management of the Urdaibai River Basin, a Biosphere Reserve in the Basque Country (Northern Spain). The overall design (multicriteria appraisal + public participation) was the same in all three cases. However, different purposes of the

respective studies lead to some differences in the type of stakeholders participating, in the knowledge brought into the process and information presented during the workshops. Due to the local nature of the Austrian case study, participating stakeholders were mostly lay-persons. However, the group had already gathered a substantial amount of information during the application for e5 funding. Some new information was introduced by inviting experts to the workshops, but the focus in the current study was on finding ways to focus and organize the use of funds that the municipalities had been awarded. While the focus of the UK case study was on the Southeast England region, energy policy is largely national in the UK, which is why participants included national and regional stakeholders. All but one participant were professionals working on energy, rural development, conservation and economic development. In contrast to the Austrian case, group discussions were geared more towards exploration rather than finding consensus. For example scoring and weighting were undertaken individually here, with group discussions to exchange information and views during the process. In the Spanish case participants were local, regional and national stakeholders. Experts from various academic disciplines (geology, engineering, sociology, law, biology, ecology and economics) introduced a wealth of information during the workshops that had previously been unfamiliar to most participants. 4.1. Data Collection To study the form and extent of social learning in stakeholder workshops that are part of sustainability appraisal, for each case study we collected data by use of Likert scale (1 to 7, with 7 being the maximum) based on questionnaires (see Appendix A1) at the beginning of the first and at the end of the final deliberative workshop. The questionnaire asks questions related to Hypotheses 1–4. In all the cases participants of the stakeholder workshops were identified by searching for those who have the highest influence on a decision plus those who are most affected by a decision. In June 2005 14+ citizens, mayors, e5-team6 and other stakeholders in Raabau and Lödersdorf in Austria took part in two workshops and a final meeting where recommendations were presented. In June and November 2008 12+ stakeholders 6 “e5” is a programme for assessing and certifying local communities with respect to their attempts (relative to their potentials) to use energy more efficiently and to intensify the use of renewable energy as a contribution to a sustainable development (www.e5-gemeinden.at).

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from UK and regional government bodies and civil society organizations participated in two workshops. From May 2007 to June 2008 three workshops with 20+ participants were held in Urdaibai in Spain; additionally over 30 personal interviews provided in-depth information about sustainable management options for the Urdaibai River Basin. In the Spanish case participants included stakeholders from the local, regional and national governments; an ecologist, bird watchers, representatives from tourism and scientific community, shipyard industry, fishermen, surfers, NGOs, mayors and citizens (Garmendia et al., 2007). Sample sizes of the data reported here turned out lower than the number of participants, because it was not always possible for the same person to represent an organization (e.g. maternity leave, other demands on one's time at short notice), which made it impossible to compare responses, and not all participants who attended all workshops completed both questionnaires.

5. Results Given the small sample size, we use Wilcoxon non-parametrical test for two related samples together with other descriptive statistics to test our hypotheses (see tables in Appendix A2). For the same reason the results presented here should be considered with caution as the research is experimental and exploratory. Further research is required to test the robustness of the findings and conclusions. However, this limitation is inherent in the nature of participatory processes as they involve normally a rather small number of participants. To address this problem somewhat we collected data from three case studies. Hypothesis 1 deals with the acquisition of different types of cognitive knowledge: By use of data from questions 1–3 of the questionnaire we find differences among the three case studies. While in the Austrian case study we do not find any significant change after the process (probably due to the high level of knowledge held by participants before the workshop), in the UK and Spain cases we observe significant changes. In the UK case, all participants consider an increase in their effectiveness knowledge after the workshop (Q3) and mean value of response change from 3.83 to 5.5. In Spain we observe a significant change in the declarative knowledge (Q1) with a .997 degree of credibility (75% of participants consider that their knowledge has increased after the workshop, and just one participant (6%) considered his knowledge as unchanged during the process). In all the three cases the standard deviation of the group responses, decreased after the workshop. In other words, in relation to the acquisition of new facts, it seems that the workshops facilitated in two out of three cases the acquisition of new facts (the simplest form of learning) and they reduced the differences between participants’ perceived knowledge. Hypothesis 2.1 deals with the framing of an issue and with the perception of the issue: Being interested in how participants consider the issue at hand, we observe in all cases that the weights attached to social parameter (Q5) have increased after the workshop, although this change is significant in the Austrian case study only. In the Spanish and UK case studies there was a significant decrease in the weight attached to economic parameter (Q4), with a credibility of over 95% according to the Wilcoxon test. Technical questions (Q6) remained least important in all the cases before and after the workshop. Participants did not change their perception about the contribution and role the following actors have in their case (Q7 scientist, Q8 politicians, Q9 civil society). Similarly, there was no significant change in the interests that support or hinder transitions to sustainability (Q10 economic interests, Q11 environmental protection, Q12 national security, etc). With regard to the standard deviation we cannot observe a clear pattern. In all three cases this parameter increases and decreases in different ways. It is not possible to state that the groups achieved a higher consensus on how to reframe the issue, after the workshop.

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Hypothesis 2.2 is concerned with the understanding of the other participants' viewpoints: In this regard, in the Austrian and UK case study there is no clear evidence that the workshop increased the familiarity or mutual understanding among participants, which may have been due to time constraints. By contrast in the case of Spain, where a longer process took place with further opportunities for interaction among the stakeholders, we observe a significant increase in the understanding of other participants’ perception after the workshop (Q13). With 99% of credibility according to Wilcoxon test, 75% of participants (12) acknowledge an increase in their knowledge about the others’ points of view. Hypothesis 2.3 considers whether participants refine their knowledge about societal needs, esp. future generations and non-human species: In none of the three case studies we find any significant change in participants’ perceptions about the relevance of future generations (Q14) and non-human species (Q15). They were high before the workshops and remained high. Hypothesis 3 deals with participants’ views about the complexities and uncertainties in the relevant systems: On a scale from ‘very straight forward’ to ‘extremely complex’ participants considered their respective problem as rather complex (Q16) with means of 6.0 in the UK, 4.2 in Austria and 4.8 in Spain. There was no significant change in relation to these perceptions about complexity. On a scale from ‘extremely uncertain’ to ‘certain’ responses were leaning toward certainty (Q17); means were 4.5 in the UK, Austria 5.6 and 5.0 in Spain. Again, there were no significant changes. Hypothesis 4 considers whether participants find ways to change institutions and to engage in joint action. In relation to institutions (Q18) there was no significant change in any of the three cases; in all cases, participants considered existing institutions as rather inadequate (means of 3.33 for UK, 3.7 for Austria and 4.06 for Spain). With regards to joint action (Q19), in the Spanish case study there was a significant change of participants’ perceptions after the workshop with a .91% degree of credibility. 62.5% of participants saw more opportunities for joint action after the workshop. In the Austrian case study, although we cannot compare ex-post responses with ex-ante responses, 63% of participants were optimistic about the possibility for joint action afterwards. With regards to dealing with conflict, in all three case studies before the workshops providing better information (Q20) was seen as the best way to deal with conflict followed by the need of a constructive dialogue (Q22) and the need to find compromises (Q21). After the workshop the call for better information decreased in the UK and Austria and became secondary in Spain. In the case of Austria this change is significant with 95% of credibility. After the workshop the search for compromise solutions was suggested as the best way to deal with conflict. Constructive discussion: In both cases (Austria and Spain)7 participants considered the participatory process during the workshops as having led to constructive discussions (Q23), with mean values of 4.89 for Austria and 6.44 for Spain. In the Spanish case the change from expectations to post-workshop assessment is significant with (99% of credibility). In both cases standard deviations have reduced significantly and it seems that there was widespread agreement with regard to this statement. Participants are considering the possibility to apply the methodology from the case studies in different settings (Q24), in Austria with a mean value of 5.12 and in Spain 6.25. In the latter case there is a significant change after the workshop with .99% of credibility. The quantitative surveys were complemented by qualitative data collection, the extent of which varied between the three cases. In Austria group discussions and reflections were not recorded, while they were in the UK. In Spain after the process open-ended interviews with 10 participants were undertaken to get a final feedback. 7 In the UK case study Q23, Q24 and Q25 were addressed as part of a group discussion at the end of the second workshop. Results are therefore not directly comparable.

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The following quotes of some participants, at the end of the several participatory processes, summarize common perceptions: “I did not know that we have all this on our backyard; we live in ignorance of the richness and diversity of the estuary's ecosystem and the workshops have been helpful for me to learn about our surrounding area.” (Participant 7, Local Development Agency, Spain). “More experiences like this one would be desirable in order to build bridges between the different actors and to know about others’ views. This facilitates the collective discussion about issues that affect all of us.” (Participant 3, Environmental Guide, Spain). “It was useful to hear other people's views about the different paths that the energy system in our region might take.” (Participant 4, Environmental NGO, UK). “What I liked about the process was that it offered a lot of information, but it didn't force us to accept anybody else's views. Instead it offered sufficient opportunity to explore different ways of doing things.” (Participant 5, Government Body, UK). 6. Discussion and Concluding Remarks The expected and assumed social learning in public participation and adaptive management has recently received much attention. However, detailed analyses of the array of potential learning processes and their outcomes are still missing. While there is plenty of anecdotal evidence of social learning, more systematic evaluations are needed to understand the social learning processes and to improve workshop designs to foster social learning. Drawing on own data from three case studies, we find that social learning does happen in participatory workshops, but (1) to a lesser extent than expected and (2) the depth and breadth of learning depends on the workshop design, time given to the process and the type of participants. The change in cognitive knowledge was significant in the UK and Spain; in Austria the increase in the mean value of expressed knowledge was not significant. The latter result may be due to the fact that the local stakeholders had come a long way in presenting their case for funding a more sustainable local energy system. In this process they explored the local potential and options in more depth than what experts who were unfamiliar with the local circumstances could have known. Hypothesis 2.1, which deals with framings and perceptions of issues, in all three cases participants attached after the workshops more relevance to social parameters in the processes of change towards more sustainable futures. This indicates that participants have expanded their concern of social obstacles for a transition to sustainability during the deliberative process. In the Spanish and UK cases this increase of the social dimension was accompanied by a significant decrease in the weight attached to economic parameters. Nevertheless when asked about the contribution of different actors their perception did not change during the process. Hence, participants seem to change their perception of the structure or framing of the problem but this perceived change did not filter through to roles and agency in decision processes. Concerning Hypothesis 2.2, the increase of participants’ mutual understanding was significant only in the Spanish case study. The wider opportunity for interaction and deliberation, i.e. more time for discussion (four workshop and a continuous feedback during two years) could be a key factor to fostering mutual understanding as other authors have suggested (Mostert et al., 2007). In relation to complexity and uncertainty (Hypothesis 3) participants acknowledged some degree of complexity and perceive the consequences of possible changes as rather certain. It would be interesting to follow up with further empirical research whether perceived complexity and uncertainty differ for issues that are national or international rather than local or regional.

For finding ways for changing institutions (Hypothesis 4), participants highlighted their limitations in doing so. Hence, the workshops did not empower participants to act as change agents; on the other hand it also indicates that the discussion remained on realistic grounds given that most of the policies discussed are decided on the national level while the case study areas were on local or regional levels. After the workshops stakeholders did perceive more opportunities for joint action with participants, which may make them more effective within the existing institutional context and joint actions can also be the seeds for changing institutions in the future. Interviews in the Spanish case study, reveal a link between responses to the joint action question and higher mutual understanding and a more respectful environment that emerged during the process. “We saw fishermen and bird watchers as enemies, and now we know that we share a lot of interest, we should row in the same direction” (Participant 2, Surfer). Real joint action happened in the Austrian case after finishing the project. The two communities involved in the ARTEMIS project,8 Raabau and Lödersdorf worked within the e5 program aiming to become sustainable communities in the energy field and stakeholders acknowledged that the participatory MCE process was useful for taking related decisions. Probably due to multiple opportunities to acquire factual knowledge during the deliberations (Hypothesis 1), after the workshops participants expressed a significantly lower need for better information. Instead they suggest the need to focus on finding compromises and on constructive discussions. In this sense most participants considered the deliberative process valuable as a basis for further constructive discussions and for the possibility to apply a similar approach in different settings. “In the first workshop I could not see any light; I thought that the fishers would boycott the process. After listening to each other we created a more relaxed environment and I think it was a very fruitful discussion to find common places” (Participant 11, Mayor of the Spanish study area). Overall participants (90% of respondents) considered the workshops a positive experience (Q25) with mean values of 5.62 in Austria and 5.69 in Spain.9 Despite clarifying a priori the scope and next steps after the workshops, some concerns over the possibilities of having an impact in real world decision making remained. Several authors have suggested that social learning should be considered as an inherent property and quality criterion of participatory approaches that seek the transition to sustainability. In this paper first, we identified different dimensions of learning processes and second, applied this framework to three real case studies that combined integrated appraisal tools with participatory approaches. Given the huge amount of effort it has gone into a better understanding of social learning from a theoretical point of view, it is now time to compare theoretical frameworks critically and use and test them by gathering empirical evidence in real case studies. Limitations of the study included difficulties to gather information in participatory settings, due to time constraints. For example, more post-workshop interviews might enrich the analysis but increase time input required from participants who already invest several days in the participatory processes. Qualitative analysis of recorded videos and tapes is an alternative to avoid this extra effort from participants while enriching the analysis with different type of information.

8 ARTEMIS; Assessment of Renewable Energy Technologies on Multiple Scales: a participatory multicriteria approach. Project funded by the Austrian Science Council (FWF). 9 In the UK case study this question was addressed as part of a group discussion at the end of the second workshop. Results are therefore not directly comparable.

E. Garmendia, S. Stagl / Ecological Economics 69 (2010) 1712–1722

Another limitation of the study is that it did not explore the link between learning processes in participatory appraisals and governance processes and public policy decisions. Acknowledgements We would like to acknowledge comments on preliminary versions of this paper presented at the PATH (Participatory Approaches in Science and Technology) conference, and at the ESEE 2007 conference

Appendix A Appendix A1. Relevant sections of the questionnaire

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(Integrating Natural and Social Sciences for Sustainability). We also acknowledge gratefully funding for the ARTEMIS project from the Austrian Science Council (FWF), for the South East England project from the Economic and Social Research Council (ESRC) and for the Basque case study funding for the EKO-Lurraldea project from the Basque Environmental Ministry. We would also like to thank all participants who were involved in the case study workshops for taking the time and for their contributions. We thank very much the two anonymous reviewers for their helpful comments.

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Appendix A2. Results from questionnaires completed before and after participatory workshops in the three case studies

Mean Ba UK Case Study n=6 Q1 4 Q2 4 Q3 3.83 Q4 5.67 Q5 4.83 Q6 4.50 Q7 6 Q8 6.17 Q9 4.83 Q10 4.50 Q11 6.50 Q12 5 Q13 Q14 6.33 Q15 5.33 Q16 6 Q17 4.50 Q18 3.33 Q19 Q20 5.17 Q21 4.17 Q22 4.5 Q23 Q24 Q25

Std. dev Bb

Mean Ac

Std. dev Ad

Neg. dife

Pos. diff

Tid.g

Wilc. testh

1.265 1.549 1.722 .516 1.169 1.643 .894 .983 .753 1.378 .548 1.265

4.50 4.17 5.50 4.5 5.33 4.33 5.33 6 4.33 4.83 6.67 4

1.049 .983 1.225 1.049 1.366 1.506 1.506 .894 1.366 1.169 .516 1.265

0 1 0 4 1 3 2 2 4 0 0 5

3 2 6 0 3 1 0 1 1 2 1 1

3 3 0 2 2 2 4 3 1 4 5 0

.083 .564 .026 .066 .257 .750 .180 .564 .180 .157 .317 .096

1.033 1.211 .632 1.049 1.211

5.83 4.33 6.17 4.67 3.50

1.169 1.366 .753 1.211 1.378

2 4 1 1 1

1 1 2 2 2

3 1 3 3 3

.414 .157 .564 .564 .564

1.722 1.472 1.378

4.67 4.33 5.17

1.033 1.211 1.722

3 1 1

1 3 4

2 2 1

.257 .705 .492

Austrian Case Study n=9 Q1 5.33 .707 Q2 5.11 .782 Q3 4.56 1.014 Q4 5.44 1.014 Q5 3.50 1.069 Q6 2.62 1.768 Q7 5.56 1.236 Q8 5.56 1.13 Q9 5.00 1.581 Q10 4.67 1.323 Q11 6.22 .833 Q12 5.00 1.323 Q13 Q14 5.56 1.59 Q15 4.89 1.616 Q16 4.22 1.856 Q17 5.56 .726 Q18 3.7 1.325 Q19 Q20 6.22 .833 Q21 4.22 .972 Q22 5.44 1.014 Q23 4.44 1.454 Q24 Q25 Urdaibai Case Study (Spain) n = 16 Q1 4.19 .981 Q2 Q3 Q4 5.70 1.525 Q5 4.40 1.536 Q6 3.55 1.701 Q7 5.75 1.125 Q8 6.38 .957 Q9 5.81 1.109 Q10 Q11 Q12 Q13 4.25 1.693 Q14 6.00 .966

Appendix A2 (continued)

Q15 Q16 Q17 Q18 Q19 Q20 Q21 Q22 Q23 Q24 Q25

Mean Ba

Std. dev Bb

Mean Ac

Std. dev Ad

Neg. dife

5.63 4.81 5.13 4.06 5.14 5.88 5.56 5.63 5.06 5.00

1.088 1.424 1.025 1.769

6.13 4.69 5.00 3.50 6.00 6.13 6.25 5.81 6.44 6.25 5.69

.806 1.702 .73 1.506 .873 1.025 .856 1.276 .814 .856 .873

2 6 6 6 3 2 2 4 0 1

1.025 1.094 1.088 1.731 1.633

Pos. diff

Tid.g

Wilc. testh

6 5 4 3 10 4 9 6 10 10

8 2 6 7 3 10 5 6 6 5

.107 .783 .713 .142 .097 .395 .022 .565 .004 .006

The questionnaires were adapted to the specific purpose and context of each case study. Not all questions were included in the surveys of all three case studies. This is the reason for blank boxes in the tables included in Appendix A2. a Mean value of responses in the questionnaire completed before the workshop. b Standard deviation of responses before the workshop. c Standard deviation of responses after the workshop. d A: Standard deviation of responses after the workshop. e Number of participants that change their response in this question to a lower value on the Likert scale. f Dif: how many participants change their response in this question to a higher value on the Likert scale. g Tid: tides in the responses. How many participants give the same response in this question before and after the workshop? h Wilc Test: Wilcoxon Test for non-parametrical two related samples, Asymp. Sig (2tailed).

References

5.44 5.22 5.33 5.11 4.33 3.13 5.00 4.78 5.44 4.38 6.33 5.33 4.25 5.33 4.33 4.11 5.78

.726 .667 .866 .928 1.093 .641 1 1.394 .882 1.408 .707 1.118 1.438 .866 1.118 1.167 .441

2 1 1 2 0 1 5 4 1 2 1 3

3 2 5 0 4 3 2 0 3 3 3 3

4 6 3 7 4 3 2 5 5 3 5 3

.783 .785 .167 .180 .024 .414 .160 .066 .257 .680 .705 .518

4 3 6 1

2 1 2 3

3 5 1 5

.595 .197 .341 .317

4.7 5.67 4.56 5.11 4.89 5.12 5.62

1.382 1 1.13 .782 .859 .909 .804

3 2 4 1

0 4 2 5

6 3 3 3

.059 .334 .334 .279

5.31

.946

1

12

3

.003

4.06 5.00 3.06 5.88 5.38 5.94

1.879 1.673 1.436 .957 1.928 1.063

11 5 10 2 7 4

2 10 4 4 2 7

3 1 2 10 7 5

.008 .667 .190 .589 .080 .647

6.13 6.06

.885 .998

1 4

12 5

3 7

.003 .739

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