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Learning in polycentric governance: Insights from the California Delta science enterprise

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Abstract

Science is critical for learning and adaptation of policy and governance systems. Increasingly, science is produced in the context of a science enterprise: a complex, polycentric institutional arrangement featuring multiple science forums and actors. The characteristics of these polycentric systems can influence whether and to what extent science supports policy‐relevant learning. Limited research, however, has examined how science enterprises function as polycentric systems and how they can be governed to support learning. Using a survey of actors involved in the science enterprise of the California Delta, we integrate the collective learning framework and ecology of games framework to analyze individual‐ and forum‐level drivers of perceived learning across the adaptive management cycle. The results suggest that social drivers such as leadership, trust, and engagement are most highly correlated with perceived learning. While science enterprise actors often perceive administrative and financial resource limitations, those constraints are less important for learning than social drivers.

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Learning is critical for land management agencies implementing new policies in the face of rapid social and ecological change. We investigated learning in the U.S. Forest Service as it implemented new planning regulations. Our research objectives were to: (1) identify collective learning processes and outcomes during this time, and (2) understand factors within the organization supporting or impeding learning. Based on participant observation and 25 interviews with planning personnel, we found evidence of collective learning on individual national forests and across the organization. Several factors helped the agency act as a ‘learning organization,’ including internal networks and tools for information sharing, and meetings for staff to exchange lessons learned. Learning was compromised by limited time and capacity, and lack of internal clarity about balancing the desire for innovation with the need to ensure legal compliance and meet deadlines. This work contributes to the empirical foundations of collective learning theory, allowing us to identify learning processes and outcomes at multiple levels in a public organization, and identifying topics for future research. Based on our exploration of organizational learning, we offer suggestions for how to effectively support learning during times of new policy implementation.
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Collaborative governance processes have become a popular mechanism for addressing complex environmental problems. Their success is premised, in part, on the assumption that they promote learning among diverse participants, who are then better equipped to develop creative, consensus-oriented environmental management actions. Significant gaps remain, however, in our understanding of how collaborative governance processes foster learning and what impact increased learning has on policymaking outputs. To investigate these relationships, this study provides one of the first empirical applications of Heikkila and Gerlak's collective learning framework. Key framework concepts are operationalized via interview data and existing literature and then measured via survey data collected from participants in a collaborative environmental governance process in Colorado, U.S. Findings indicate that both internal and exogenous contextual factors affect how much an individual learns within a collective context. Additionally, participants who report more learning also more strongly agree that the process produced favorable outputs and outcomes. These findings advance theories of learning in collaborative contexts and inform process design to maximize learning.
Article
Throughout the last two decades, Bayesian statistical methods have proliferated throughout ecology and evolution. Numerous previous references established both philosophical and computational guidelines for implementing Bayesian methods. However, protocols for incorporating prior information, the defining characteristic of Bayesian philosophy, are nearly nonexistent in the ecological literature. Here, I hope to encourage the use of weakly informative priors in ecology and evolution by providing a “consumer's guide” to weakly informative priors. The first section outlines three reasons why ecologists should abandon noninformative priors: (1) common flat priors are not always noninformative, (2) noninformative priors provide the same result as simpler frequentist methods, and (3) noninformative priors suffer from the same high Type I and Type M error rates as frequentist methods. The second section provides a guide for implementing informative priors, wherein I detail convenient “reference” prior distributions for common statistical models (i.e. regression, ANOVA, hierarchical models). I then use simulations to visually demonstrate how informative priors influence posterior parameter estimates. With the guidelines provided here, I hope to encourage the use of weakly informative priors for Bayesian analyses in ecology. Ecologists can and should debate the appropriate form of prior information, but should consider weakly informative priors as the new “default” prior for any Bayesian model. This article is protected by copyright. All rights reserved.
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en Collaborative governance processes seek to engage diverse policy actors in the development and implementation of consensus‐oriented policy and management actions. Whether this is achieved, however, largely depends on the degree to which actors with different beliefs coordinate their actions to achieve common policy goals—a behavior known as cross‐coalition coordination. Drawing on the Advocacy Coalition Framework and collaborative governance literatures, this study analyzes cross‐coalition coordination in three collaborative environmental governance processes that seek to manage water in the Colorado River Basin. Through comparative analysis, it highlights the complex relationship among the institutional design of a collaborative governance process, how and why actors choose to engage in cross‐coalition coordination, and the consequent policy outputs they produce. The findings advance policy scholars’ nascent understanding of cross‐coalition coordination and its potential to affect policymaking dynamics. Abstract zh 协作治理流程, 旨在让各种政策行为者参与制定并实施以共识为导向的政策和管理行动。然而, 这是否能够实现, 在很大程度上取决于, 具有不同信仰的行动者会在多大程度上协调他们的行动以实现他们共同的政策目标——这种行为称为跨联盟协调。借助倡导联盟框架(Advocacy Coalition Framework)和协作治理领域的文献, 本研究观察了三个旨在管理科罗拉多河流域水资源的协作环境治理过程, 分析了其中的跨联盟协调。通过比较分析, 本文突出强调了协作治理流程的制度设计、行为者选择参与跨联盟协调的方式和原因、以及它们所带来的政策产出这几者之间的复杂关系。这些发现推动了政策学者对跨联盟协调的初步理解, 增强了对跨联盟协调影响政策制定动态这一潜在问题的认识。
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Collaborative governance By its nature, environmental governance requires collaboration. However, studies have shown that various types of stakeholders often lack the willingness to deliberate and contribute to jointly negotiated solutions to common environmental problems. Bodin reviews studies and cases that elucidate when, if, and how collaboration can be effective and what kind of environmental problems are most fruitfully addressed in this way. The piece provides general conclusions about the benefits and constraints of collaborative approaches to environmental management and governance and points out that there remain substantial knowledge gaps and key areas where more research is needed. Science , this issue p. eaan1114
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Scholarship on collaborative governance identifies several structural and procedural factors that consistently influence governance outcomes. A promising next step for collaborative governance research is to explore how these factors interact. Focusing on two dimensions of social learning—relational and cognitive—as outcomes of collaboration, this article examines potential interacting effects of participant diversity and trust. The empirical setting entails 10 collaborative partnerships in the United States that provide advice on marine aquaculture policy. The findings indicate that diversity in beliefs among participants is positively related to relational learning, whereas diversity in participants' affiliations is negatively related to relational learning, and high trust bolsters the positive effects of belief diversity on both relational and cognitive learning. In addition, high trust dampens the negative effects of affiliation diversity on relational learning. A more nuanced understanding of diversity in collaborative governance has practical implications for the design and facilitation of diverse stakeholder groups.
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Recommendations for improving environmental management often advocate a holistic approach that supports both social and environmental objectives. This should be reflected in approaches to monitoring and evaluation; however, monitoring is often inadequate and hence limits our ability to implement adaptive management. It is important to understand if monitoring practices are changing, and if not, why. Thus, this paper considers the monitoring practices and priorities of 24 ‘Ecosystem Approach’ projects implementing holistic and participatory environmental management. We found project monitoring was often focused on biophysical indicators, such as indicators of water pollution, even when adaptive management might prioritize understanding different issues or using different data-types. By contrast, aspects of social and economic aspects were monitored infrequently. Procedural aspects were rarely tracked. Project managers' aspirations did sometimes include such issues, but these were seen as more difficult or even impossible to measure. Schema were also shaped by the need to demonstrate accountability and quantify progress to funders. Our study suggests monitoring still falls short of theoretical recommendations. This is partially due to the misfit between new understandings of socio-ecological systems and pre-existing modernist paradigms, whose conceptions and expectations still have pervasive effects of our ways of thinking and working. Tackling this requires explicit attention to sticking points across the levels of institutions that shape environmental management. Copyright © 2017 John Wiley & Sons, Ltd and ERP Environment
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Research on collective recall takes on new importance in a post-fact world.
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Adaptive management is appraised as a policy implementation approach by examining its conceptual, technical, equity, and practical strengths and limitations. Three conclusions are drawn: (1) Adaptive management has been more influential, so far, as an idea than as a practical means of gaining insight into the behavior of ecosystems utilized and inhabited by humans. (2) Adaptive management should be used only after disputing parties have agreed to an agenda of questions to be answered using the adaptive approach; this is not how the approach has been used. (3) Efficient, effective social learning, of the kind facilitated by adaptive management, is likely to be of strategic importance in governing ecosystems as humanity searches for a sustainable economy.
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Collaborative approaches to environmental and natural resource management are on the rise in the United States. This article examines collaborative governance in four high-profile and large-scale ecosystems: the Northwest Power and Conservation Council's Fish and Wildlife Program in the Columbia River Basin, the Chesapeake Bay Program, the CALFED Bay-Delta Program in California's San Francisco Bay/ Sacramento-San Joaquin River Delta, and the Florida Everglades Restoration Program. We compare the governance structures of these four institutional arrangements by examining how collaboration occurs or is organized at three different levels of decision making: constitutional, collective choice (or policymaking), and operational (or implementation). This includes an examination of governance and advisory bodies as well as coordinating and monitoring structures.
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Academics and policy makers in many Western countries are perceived as occupying separate communities, with distinct languages, values, and reward systems. However, data from a survey of more than 2,000 policy officials and 126 in-depth interviews with public servants in Australia suggest that the “two communities” conceptualization may be misleading and flawed. More realistically, there is a range of interaction between policy and academia, with some individuals valuing and using academic research more than others. Furthermore, this relationship is complicated by the internal division between the political and administrative components of the public policy process.
Article
Fuzzy Cognitive Maps (FCM) have found favor in a variety of theoretical and applied contexts that span the hard and soft sciences. Given the utility and flexibility of the method, coupled with the broad appeal of FCM to a variety of scientific disciplines, FCM have been appropriated in many different ways and, depending on the academic discipline in which it has been applied, used to draw a range of conclusions about the belief systems of individuals and groups. Although these cognitive maps have proven useful as a method to systematically collect and represent knowledge, questions about the cognitive theories which support these assumptions remain. Detailed instructions about how to interpret FCM, especially in terms of collective knowledge and the construction of FCM by non-traditional ‘experts’, are also currently lacking. Drawing from the social science literature and the recent application of FCM as a tool for collaborative decision-making, in this chapter we attempt to clarify some of these ambiguities. Specifically, we address a number of theoretical issues regarding the use of Fuzzy Cognitive Mapping to represent individual “mental models” as well as their usefulness for comparing and characterizing the aggregated beliefs and knowledge of a community.
Article
The search for strategies to address ‘super wicked problems’ such as climate change is gaining urgency, and a collaborative governance approach, and adaptive co-management in particular, is increasingly recognized as one such strategy. However, the conditions for adaptive co-management to emerge and the resulting network structures and relational patterns remain unclear in the literature. To address these identified needs, this study examines social relationships from a network perspective while initiating a collaborative multiactor initiative aimed to develop into adaptive co-management for climate change adaptation, an action research project undertaken in the Niagara region of Canada. The project spanned 1 year, and a longitudinal analysis of participants’ networks and level of participation in the process was performed. Evidence of support for climate change adaptation from the process included the development of deliberative and adaptive responses to opportunities presented to the group and the development of a strong subgroup of participants where decision-making was centered. However, the complexity of the challenge of addressing climate change, funding constraints, competing initiatives, and the lack of common views among participants may have contributed to the group, highlighting the finding that beneficial network structural features and relational patterns are necessary but not sufficient condition for the development of an adaptive co-management process. The context of climate change adaptation may require a different social network structure and processes than other contexts for adaptive co-management to occur, and there may be limitations to adaptive co-management for dealing with super wicked problems.
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Collaborative governance and organizational networks are popular and well-documented topics, but the relationship between them is not always clear. In this paper, we examine the extent to which publicly sponsored collaborative groups are associated with network ties between individual organizations by applying exponential random graph models to model how co-membership and co-participation in a publicly sponsored collaborative group is associated with the likelihood of two organizations engaging directly in three types of network ties: consultation, planning, or management. Our data come from a member survey of 57 collaborative groups that involve independent public, nonprofit, and private organizations in collective efforts to restore marine areas and freshwater ecosystems. We find that the probability of observing a network tie between two organizations increases with the extent to which both organizations participate in the same collaborative group, but that this association diminishes as organizations belong to an increasing number of groups. This association is strongest for organizations that report that their participation in a collaborative group has increased their access to information and resources and increased their awareness of other organizations. Given that public agencies often seek to use collaborative groups as a means by which to foster relationships between organizations in a policy network, it is important to know whether the initiation and sponsorship of collaborative groups is associated with the formation of inter-organizational network ties.
Article
This paper provides an overview of our adaptation of Norton Long's concept of the “ecology of games” into a theoretical framework for analyzing institutional complexity. I discuss the basic concepts of the framework, discuss hypotheses related to fundamental questions in governance and policy, and outline some basic analytical approaches. The conclusion assesses the future prospects of the ecology of games framework, including future research needs for theoretical and empirical development.
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In public policy processes, collective learning among policy actors is important in shaping how these processes unfold and the types of policy outcomes that may result. Despite a widespread interest in learning by policy scholars, researchers face a number of conceptual and theoretical challenges in studying learning across different collective settings within policy processes. In this article, we offer a theoretically grounded approach to defining and understanding collective‐level learning. In defining learning, we first draw out the connection between learning processes and learning products, both cognitive and behavioral. In examining learning processes, we further explore the relationship between individual and collective learning. Then we identify and define the key characteristics of collective settings that will likely influence learning processes. We conclude by offering recommendations for policy scholars to apply this approach in studies of learning across diverse policy contexts.
Article
The field of policy learning is characterised by concept stretching and a lack of systematic findings. To systematise them, we combine the classic Sartorian approach to classification with the more recent insights on explanatory typologies, distinguishing between the genus and the different species within it. By drawing on the technique of explanatory typologies to introduce a basic model of policy learning, we identify four major genera in the literature. We then generate variation within each cell by using rigorous concepts drawn from adult education research. By looking at learning through the lenses of knowledge utilisation, we show that the basic model can be expanded to reveal sixteen different species. These types are all conceptually possible, but are not all empirically established in the literature. Our reconstruction of the field sheds light on mechanisms and relations associated with alternative operationalisations of learning and the role of actors in the process of knowledge construction and utilisation. By providing a comprehensive typology, we mitigate concept-stretching problems and lay the foundations for the systematic comparison across and within cases of policy learning.
Article
Allusions to the “problem of metropolitan government” are often made in characterizing the difficulties supposed to arise because a metropolitan region is a legal non-entity. From this point of view, the people of a metropolitan region have no general instrumentality of government available to deal directly with the range of problems which they share in common. Rather there is a multiplicity of federal and state governmental agencies, counties, cities, and special districts that govern within a metropolitan region. This view assumes that the multiplicity of political units in a metropolitan area is essentially a pathological phenomenon. The diagnosis asserts that there are too many governments and not enough government. The symptoms are described as “duplication of functions” and “overlapping jurisdictions.” Autonomous units of government, acting in their own behalf, are considered incapable of resolving the diverse problems of the wider metropolitan community. The political topography of the metropolis is called a “crazy-quilt pattern” and its organization is said to be an “organized chaos.” The prescription is reorganization into larger units—to provide “a general metropolitan framework” for gathering up the various functions of government. A political system with a single dominant center for making decisions is viewed as the ideal model for the organization of metropolitan government. “Gargantua” is one name for it.