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Robin Gregory

Publications and source records attributed to Robin Gregory.

3 recordsLinked to original sources

Learning as an objective within a structured risk management decision process.

Social learning through adaptive management holds the promise of providing the basis for better risk management over time. Yet the experience with fostering social learning through adaptive management initiatives has been mixed and would benefit from practical guidance for better implementation. This paper outlines a straightforward heuristic for fostering improved risk management decisions: specifying learning for current and future decisions as one of several explicit objectives for the decision at hand, drawing on notions of applied decision analysis. In keeping with recent guidance from two important U.S. advisory commissions, the paper first outlines a view of risk management as a policy-analytic decision process involving stakeholders. Then it develops the concept of the value of learning, which broadens the more familiar notion of the value of information. After that, the concepts and steps needed to treat learning as an explicit objective in a policy decision are reviewed. The next section outlines the advantages of viewing learning as an objective, including potential benefits from the viewpoint of stakeholders, the institutions involved, and for the decision process itself. A case-study example concerning water use forfisheries and hydroelectric power in British Columbia, Canada is presented to illustrate the development of learning as an objective in an applied risk-management context.

Animals↗

Testing alternative decision approaches for identifying cleanup priorities at contaminated sites.

This exploratory study compares two approaches for involving nonexpert stakeholders in difficult policy choices. Both approaches have as their goal informing members of the public about contaminated sites and involving them in decisions regarding their cleanup. The first approach focuses on technical information and seeks to improve the available knowledge base so that participants can make choices informed by detailed scientific data. This approach is similar in intent to many of the science-based initiatives in public involvement now being undertaken by EPA, DOE, and other federal or state agencies. The second approach, in contrast, focuses on values-oriented information and seeks to improve stakeholders' ability to make difficult choices in light of required tradeoffs across a variety of technical and nontechnical concerns. The results demonstrate that although both approaches help to increase participants' knowledge level, a values-based approach is more successful in terms of helping nonexpert participants to make decisions aboutwhat have historically been viewed as primarily technical problems.

Decision Making↗

Ten common mistakes in designing biodiversity indicators for forest policy.

This paper identifies 10 common 'mistakes' in developing and using forest biodiversity indicators from the standpoint of making better forest management choices. The mistakes relate to a failure to clarify the values-basis for indicator selection and a failure to integrate science and values to design indicators that are concise, relevant and meaningful to decision makers. The combined effects of these ten mistakes include inconsistent and indefensible on-ground management strategies and hidden trade-offs at a policy level. They result in frustrated professionals, a confused public, an inability to assess performance with respect to key forest policy objectives and, almost certainly, types and amounts of biodiversity conservation that fail to achieve either scientifically or socially preferred levels. Correcting the mistakes will help to address these problems and, more generally, recognizes the need to better understand the interface between science, public values, and decision making.

Conservation of Natural Resources↗