Improving Expert Elicitation Through Studies of Climate Change and Its Possible Impacts

通过气候变化及其可能影响的研究改进专家启发

• 批准号: 9209783
• 负责人: M Granger Morgan
• 金额: $ 10.5万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1992
• 资助国家: 美国
• 起止时间: 1992-10-01 至 1997-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9209783&HistoricalAwards=false
• 关键词: Improving; Expert; Elicitation; Through; Studies

The science of global climate change and its impacts is dominated by uncertainty. Public policy decisions require near term scientific judgments, since the scientific facts will not be known for years. This study conducts research on the elicitation of expert judgment in the context of the global ecological impacts of climate change. The study generalizes elicitation methods by asking experts to structure the issues, propose a model, and the give judgments about the important parameters of their model. This approach gives the experts more latitude to express their views compared to prior work in expert judgment. A two-stage elicitation process is used to elicit the expert's views about: (1) the structure, the metric(s), and the value of key uncertain coefficients that should be used in framing the problem; (2) the reliability of key findings in their field of expertise and in other fields upon which their work depends (including the reliability of consensus reports); (3) their sensitivity to and ability to identify the potential sources of surprise; and (4) the amount of reduction in uncertainty (in their field of expertise and in other climate change related issues) that could be achieved with various amounts of research investment. These elicitations will help us to define the character of uncertainties dominating climate change issues better, shed light on how the reliability of knowledge and research is gauged within the scientific community, and provide guidance on research allocations.

全球气候变化及其影响的科学以不确定性为主。 公共政策决策需要近期的科学判断，因为科学事实多年后才会为人所知。 本研究在气候变化对全球生态影响的背景下进行专家判断的研究。 该研究通过要求专家构建问题、提出模型并对模型的重要参数做出判断来概括启发方法。 与之前的专家判断工作相比，这种方法为专家提供了更多表达观点的自由度。 采用两阶段启发过程来引出专家关于以下方面的观点： (1) 构建问题时应使用的结构、度量和关键不确定系数的值； （2）其专业领域和其工作所依赖的其他领域的主要发现的可靠性（包括共识报告的可靠性）； (3) 他们对潜在意外来源的敏感性和识别能力； (4) 通过不同数量的研究投资可以实现的不确定性减少量（在其专业领域和其他气候变化相关问题中）。 这些启发将帮助我们更好地定义主导气候变化问题的不确定性的特征，阐明科学界如何衡量知识和研究的可靠性，并为研究分配提供指导。