Special to The Denisonian

Albert Einstein once said, the myth goes, “Not everything that counts can be counted, and not everything that can be counted counts.” This adage is how Dr. Larry Sherman ‘70, began his lecture on Thursday night.

Sherman’s talk was entitled, “Counting What Counts in Justice: Policing, Race, and the Rule of Law.” Sherman illustrated the problematic “dialectic” in his area of research- just how much policing is enough policing? Or conversely, how much policing is too much policing? This difference is the fine line between a police force that is too absent and allows crime to surge, and one that is too intrusive and fosters bad blood with the community.

These types of questions are hard to objectively measure, as he indicates through Einstein’s quote, but Sherman has proven that through meticulous work he can show otherwise. Much of Sherman’s research centers around this fundamental idea.

“Larry is a really smart guy, he’s really knowledgeable about this stuff,” Danny Song ‘17 said, a Computer Science major from Columbus. “He visited our math modeling class to talk about data analytics and how certain data can shape society’s perceptions of specific issues.” This might well be the importance of Sherman’s work, condensed into a single sentence.

Reform is most efficacious when it is rooted in the tangible and the objective. It is for this reason exactly that Denison, with the help of Dr. Sherman, is in the process of developing an entirely new data analytics major.

This major will focus specifically on the methodology and impetus for this work through modeling trends, predicting patterns and mobilizing reform policy.

The major will consist heavily of math courses already offered here at Denison, but in addition will be adding unique “data analytics” courses along with a handful of new staff.

In the field of data analytics, numbers rule.

When approaching this issue, this is exactly what Sherman turns to find answers. He suggests counting, and counting with big numbers, when investigating police homicides. The larger the pool of data to draw from is, the more accurate and consistent the resultant trends tend to be.

Objections to his methodology argue that mathematical modeling “removes the human element” from police work. Sherman would offer that in fact the best results would often prove otherwise.

In a world swimming in technology, big data is the only way to accurately represent, and therefore reshape, our society.

Sherman is possibly most famous for his work in developing “evidence-based policing:” a method of police work that promotes analytical, empirical and trial-tested approaches to law enforcement.

Some of the results to come out of this research were suggestions for police officers. 

Suggestions included prioritizing de-escalation techniques in potentially violent situations, mandatory “Don’t Shoot” training exercises, barring of any and all “warning shots” and perhaps most importantly, the prohibition of firing on fleeing suspects.

It would seem that not only is Sherman invested in his work and his duty to a higher ethic, but he is also bound back here to Granville, where he is motivating some significant changes and contributing to the school’s interdisciplinary vision.

The Doris G. Gordon Lecture in Mathematics and Computational Science invites one speaker every year to talk about their work in the field of mathematics.

Sherman is currently the Wolfson Professor of Criminology at Cambridge University while also serving as the Director of the Cambridge Institute of Criminology.