Paducah Vision Paducah's Future Vision Site

Guiding Principles

The Paducah Future Vision Project was guided by four underlying principles:

1. The project was designed to incorporate the recommendations of a report entitled “The Politics of Cleanup” (ECA, 2007) that reviewed past US DOE community involvement strategies at three major DOE facilities: Rocky Flats, Mound, and Oak Ridge.
2. The project was designed to maximize citizen control, as defined in the “Ladder of Citizen Participation” (Arnstein, 1969). Not only did the ladder provide a guideline for use by the team, it served as a way to gauge public perceptions about past and current levels of community involvement, as well as preferences for future involvement.
3. A key to the potential success of the project was to involve as large and diverse a group of stakeholders as possible. Consequently, a community engagement process known as “Community-Based Participatory Communication” (CBPC) was used. CBPC has been described as “a process of raising consciousness and deep understanding about social reality, problems and solutions, rather than persuasion for short-term behavioral changes that are only sustainable with continuous campaigns” (Dagron, 2001). In particular, an attempt was made both to solicit stakeholders’ values about their local community and preferences for future uses of the PGDP property and to actively involve stakeholders in developing the overall decision-making process and scenarios for consideration.
4. Finally, the “Structured Public Involvement” (SPI) engagement process was selected to further maximize stakeholder participation, as well as to insure that the final set of possible future vision scenarios included the full range of stakeholder suggestions During the implementation of SPI, each public meeting participant is given a small keypad transmitter (about the size of a credit card) that provides the opportunity to respond anonymously to different questions. The collective feedback can be displayed instantly to all participants. The data also can provide more detailed information for analysis through something called the “Casewise Preference Model” (Bailey et. al., 2001), helping to identify clusters of stakeholder likes and dislikes, and even more importantly, predicting preferences and aversions for possible scenarios not explicitly considered. The latter capability becomes increasingly important as the complexity of land use possibilities increases, making it unrealistic for the public to evaluate all possible scenarios.