Research Principles

transparent & Unbiased statistical analysis

our framework is guided by 3 essential core principles

A better understanding of these principles helps to frame the results presented in the technical portions of the analysis. We hope by presenting these principles that readers will have a better context to understand the overall framework of our approach.

Board and advisory members present data findings.

Research Principles

Assessing racial disparities in policing data has been used for the last two decades as a policy tool to evaluate whether there exists the possibility that racial and ethnic bias is occurring within a given jurisdiction. The statistical evaluation of policing data in Connecticut is an important step towards developing a transparent dialogue between law enforcement and the public at large. As such, it is the goal of this project to present the results of any evaluation in the most transparent and unbiased manner possible. The research strategy underlying the statistical analysis presented in our reports was developed with three guiding principles in mind. Each principle was considered throughout the research process and when selecting the appropriate results to display publicly.

Evaluation Tools

Principle 1


Assists the advisory board in shaping the system for collection and analysis of traffic stop records on an annual basis. Some of its activities include determining what information should be collected, how the information is reported to the state, and the best methods for analyzing that information.

Principle 2


Public Awareness Work Group: assists the advisory board in aspects of the project that relate to informing the public of the law and results from the annual analysis. The work group helps to coordinate public awareness and outreach efforts and works to ensure that all data and analysis are accessible to the public.

Principle 3


Assists the advisory board  in aspects of the project that relate to training police agencies in the collections of traffic stop data. The work group also works to identify and implement quality bias-based policing programs for police officers.