“Investigation Reveals Inaccurate Racial Profiling Data by Connecticut State Police, No Evidence of Intentional Misconduct”

HARTFORD, Conn. – Investigation Reveals Data-Entry Mistakes, Not Intentional Bias

An independent investigation report released on Thursday has found that the inaccurate racial profiling data on traffic stops made by the Connecticut State Police was largely due to data-entry mistakes and other mishaps, rather than an intentional effort by troopers to submit false information. The investigation was ordered by Governor Ned Lamont after an audit last year identified numerous troopers who may have submitted false or inaccurate information on thousands of traffic stops to the state’s system for preventing racial profiling.

No Evidence of Misconduct

The report by independent investigators, led by former federal prosecutor Deirdre Daly, stated that while seven officers with discrepancies in their data were referred to state police internal affairs for further review, another 74 officers were found “not likely” to have committed misconduct. The investigators also concluded that there was no evidence to suggest that any trooper engaged in misconduct with the specific intent of skewing the state’s police racial profiling data.

Failures in Reporting Accurate Data

The audit conducted by data analysts at the University of Connecticut had raised doubts about the accuracy of reports on the race and ethnicity of drivers pulled over by police statewide, indicating a disproportionate number of traffic stops involving Black and Hispanic motorists. The independent investigators found “significant failures” by state police in reporting accurate data, primarily due to inadvertent errors and a lack of training for troopers, as well as failures in leadership.

Implications for Troopers and State Police Leadership

The new report disclosed that six troopers and a constable were referred to state police internal affairs investigators due to potential overreporting of the number of traffic stops they made. While no proof of misconduct was found, the reasons for the overreporting could not be determined. Additionally, state police leadership will refer between five and eight additional troopers to internal affairs because of problems with their data.

The state’s new public safety commissioner, Ronnell Higgins, expressed his concern over the potential falsification of traffic stop data and emphasized that troopers referred to internal affairs have been removed from traffic enforcement duties. If misconduct is substantiated, they could face termination and loss of their police certifications.

Continued Review and Investigation

The audit conducted by the University of Connecticut had identified 130 troopers with a significant disparity between traffic stop information submitted to the state database and the court system. Since the audit, state police have cleared nearly 90 of the troopers after reviewing their data. However, the review is still ongoing. The UConn analysts had not investigated whether the questionable data was intentionally falsified or the result of carelessness or human error.

The U.S. departments of Justice and Transportation are currently investigating the ticket data as well.

The state police union, which has been critical of the UConn audit, expressed satisfaction with the new report’s findings. Andrew Matthews, the union’s executive director and a former trooper, stated that the UConn audit had unjustifiably harmed the agency’s reputation and negatively impacted the public’s trust in law enforcement.

Steps Taken to Ensure Data Accuracy

Governor Lamont and Commissioner Higgins emphasized that several measures have already been implemented to ensure the accurate entry of data, including placing computers in all police cruisers, providing training for troopers and supervisors, and conducting regular data audits.

The independent investigation report provides further clarity on the issue of racial profiling in traffic stops made by the Connecticut State Police, highlighting the need for improved data reporting practices and training to prevent future inaccuracies.


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