SciPolicy Watchdogs: New Ways to Evaluate Policy, Anticipate Problems, and Predict Results

Historically, it has been impossible to accurately predict the success of a policy. The scientific process of conducting repeatable experiments simply does not apply to social situations. And, the historical practice of amassing data has not proved a reliable way to ensure the success of policy. Recently, we have developed Integrative Propositional Analysis (IPA) to evaluate the internal "logic structure" of policy models. This new appraoch is based on a "science of conceptual systems" perspective which has found a positive correlation between certain quantifiable structures of logic, and the ability to acheive success in a wide variety of fields from science to policy.  IPA provides an objective, non-partisan, approach to evaluating policy models. Because the model reflects the “understanding” of how the world works, IPA allows us to identify policy weaknesses before implementation. This approach also allows us to improve the policy (by improving the internal logics), compare policies (to choose the ones most likely to succeed), create an environment of policy collaboration (to generate synergy-based success), and create a framework for tracking relevant data to rigorously evaluate the policy. While this approach is orthogonal to the collection of empirical data, the two are complimentary. IPA is also orthogonal to, yet complimentary with, collaborative approaches to developing policy.  This poster session will present, compare, contrast, and integrate multiple policies – showing their structural strengths and weaknesses and clarifying opportunities for improvement through empirical research, collaboration, and strctural evaluation. By visiting this session, participants will learn a new and powerful approach to evaluating policy models that will enable them to become more effective practitioners.