Social Priorities as Data

Abstract:

Decision makers’ responses to local risks and expected changes to a community from circumstances like natural hazards, human developments, and demographic changes can greatly affect social and environmental outcomes in a community. Translating physical data based in disciplines like engineering and geosciences into positive outcomes for communities can be challenging and often results in conflict that appears to pit “science” against “the public.” Scientists can be reluctant to offer recommendations for action based on their work, often (and often correctly) noting that their role is not to make value judgments for a community – particularly for a community that is not their own. Conversely, decision makers can be frustrated by the lack of guidance they receive to help translate data into effective and acceptable action. The solution posed by this submission, given the goal of co-production of knowledge by scientists and decision makers to foster better community outcomes, is to involve the community directly by integrating social scientific methods that address decision making and community engagement to the scientist-decision maker interaction. Specifically, the missing dataset in many scientist-decision maker interactions is the nature of community priorities. Using scientifically valid methods to rigorously collect and characterize community priorities to help recommend tradeoffs between different outcomes indicated by the work of physical and natural scientists can bridge the gap between science and action by involving the community in the process. This submission presents early work on US preferences for different types of social and environmental outcomes designed to integrate directly with engineering and physical science frameworks like Life Cycle Assessment and Environmental Impact Statements. Cardinal preference data are based on surveys of US adults using tools like the Analytical Hierarchy Process, budget allocation, and ranking.