A Technical Guide for Policy Surveillance

Abstract

Law can be a powerful tool in improving population welfare. Laws can, for example, help keep people safe and healthy by encouraging the use of seat belts, or by reducing the release of toxins into our environment. Laws can also have important unintended effects, both positive and negative, or can simply fail to produce the benefits that were intended. The key to understanding the impact of the law through quantitative evaluation is to monitor changes in the law across jurisdictions, and over time, and evaluate how these changes impact population outcomes. Not only does measurement of the law allow us to understand which jurisdictions have effective laws, but it also helps us to understand the elements of policies that work best, allowing us to craft better laws that produce better results.

“Policy surveillance” is the ongoing, systematic collection, analysis and dissemination of information about laws and other policies of social importance. It is the most efficient way to measure the law, create data for analyses and disseminate information about the state of the law. The foundation of policy surveillance is the legal dataset. An empirical legal dataset is a set of quantitative measurements that represent the observable characteristics or the mechanistic features of a body of law across jurisdictions and over time. While legal and other researchers have been compiling 50-state surveys of law for decades, scientific standards and methods for creating legal mapping studies have not been developed or shared. This Technical Guide, the product of a Delphi Process conducted by PHLR, is a first attempt at codifying consensus standards and methods for the creation of scientific legal datasets and the conduct of policy surveillance. It includes guidance for setting the scope of a dataset, conducting legal research and coding, publishing datasets, updating, and quality control.

Keywords: measuring law, coding law, public health law research