White Papers

Deconstructing the Public Policy Process

How can we leverage technology platforms to increase transparency and enable citizen engagement in the public policy process?
Laws, regulations, and government programs underpin the lives of everyday citizens, but the methods through which they are created remain opaque to the average person. How can we leverage technology platforms to increase transparency and enable citizen engagement in the public policy process?

Challenges

By the time public policies make their way into mainstream news, they are already in their last stages of finalization. Often the only outstanding action is a yes or no vote on whether the policy or regulation will be enacted. Citizens are left with an understanding of which policies are being proposed but little time to change the proposals.

Although laws such as the Lobbying Disclosure Act, the Foreign Agents Registration Act, and the Honest Leadership and Open Government Act are meant to provide transparency into lobbying activities, at best they create a ledger of government contact points with little detail on what was discussed. Citizens who wish to engage in the policy development process are left guessing exactly where specific policy details originated and which players have been the most influential.

Due to this lack of transparency in the policy development process, citizen engagement efforts are primarily focused on increasing participation in elections or pressuring elected officials. However, elections are blunt instruments for influencing policy outcomes, and elected officials only represent one of the many stakeholders in the public policy process.

Our Solution

Rather than taking the traditional approach of tracking specific policy proposals or actors, Code for Democracy follows trending narratives in order to back out the policies and actors involved. By searching for changes in information flows for topic areas of interest and then matching findings with databases of proposed policies and financing disclosures, we can reverse engineer distribution timelines and channels in order to understand the goals of each actor, the relationships between them, and the optimal time to engage.