Dilling, L., and M.C. Lemos
Dilling, L., and M.C. Lemos, 2011. Creating usable science: opportunities and constraints for climate knowledge use and their implications for science policy. Global Environmental Change. 21: 680-689. doi:10.1016/j.gloenvcha.2010.11.006
In the past several decades, decision makers in the United States have increasingly called upon publicly funded science to provide “usable” information for policy making, whether in the case of acid rain, famine prevention or climate change policy. As demands for usability become more prevalent for publicly accountable scientific programs, there is a need to better understand opportunities and constraints to science use in order to inform policy design and implementation. Motivated by recent critique of the decision support function of the US Global Change Research Program, this paper seeks to address this issue by specifically examining the production and use of climate science. It reviews empirical evidence from the rich scholarship focused on climate science use, particularly seasonal climate forecasts, to identify factors that constrain or foster usability. It finds, first, that climate science usability is a function both of the context of potential use and of the process of scientific knowledge production itself. Second, nearly every case of successful use of climate knowledge involved some kind of iteration between knowledge producers and users. The paper argues that, rather than an automatic outcome of the call for the production of usable science, iterativity is the result of the action of specific actors and organizations who ‘own’ the task of building the conditions and mechanisms fostering its creation. Several different types of institutional arrangements can accomplish this task, depending on the needs and resources available. While not all of the factors that enhance usability of science for decision making are within the realm of the scientific enterprise itself, many do offer opportunities for improvement. Science policy mechanisms such as the level of flexibility afforded to research projects and the metrics used to evaluate the outcomes of research investment can be critical to providing the necessary foundation for iterativity and production of usable science to occur.