Dr. Yunliang Meng, professor of geography at CCSU, started working on racial profiling while doing a post-doc fellowship at the School of Social Work at York University in Toronto. “I am a geographer, so you might ask ‘why did you work for a school of social work?’” he said. The answer is spatial analysis: the study of geographic distribution of a given entity—in this case, stops by police.
Dr. Meng used analysis to determine whether black youths in Toronto were being “over-stopped” by police. Over-stopping is when a certain segment of the population is detained by police proportionately more frequently than other groups. Black youths are stopped three to four times more often than their white counterparts.
Armed with data released by the Toronto police department, Dr. Meng used GIS (Geographic Information Systems) software to plot the stops geographically. “I used the number of stops divided by the population in different neighborhoods to get a stop ratio,” he explained. His research has shown that yes, black youths are stopped more frequently than youths of other races. By calculating by the demographic makeup of each neighborhood rather the city as a whole, Dr. Meng was also able to determine where over-stopping was occurring. “Black youths are more likely to be searched in white and wealthy neighborhoods,” he said.
Racial profiling by Toronto police came on the radar of academics in 2002 after a series of articles alleging systemic profiling appeared in The Toronto Star, Canada’s largest newspaper. Dr. Meng started researching in 2011 after a conversation with his then colleague, Dr. Uzo Anucha of York University. “After I finished my PhD, I talked with Dr. Uzo and we were trying to figure out something we shared a common interest in. She asked me to do some social justice work in the city of Toronto,” he explained. Geographers often work with academics in other fields like social work, psychology, astronomy, and epidemiology.
Part of the racial disparity in stops could be driven by the form of problem-oriented policing used by the Toronto police. “The assumption is that the police only have limited resources: a limited number of cars, of policeman, of motorcycles, etc. However, the city is big. It is impossible to have a policeman stand at every corner or on every block. So they allocate resources disproportionately to areas they think it is needed more. But based on what? They base it on their previous crime statistics. They define where the crime hot spots exist, then they allocate more resources to that area.” This method can lead to a snowball effect. As more and more people are caught in an area due to increased policing, the hotspot seems to be getting worse, leading to more policing.
Dr. Meng stresses that his research is just the beginning. “All GIS quantitative analysis based on secondary is just preliminary. You have to recognize the limitations of our research. This data is voluntarily given over by the police… some stops could go unreported, or the police could just under-report all stop incidents,” he said. As the data hides some personal information, it is also impossible to tell how many individuals are being stopped. “A single person could be stopped multiple times and that inflates the statistics,” he explained.
The data also cannot tell the content of these stops. “Some of [the reasons for stopping] are so vague you can’t believe it; for example, ‘general investigation’ or ‘suspicious activity.’ Anything could be suspicious,” said Dr. Meng. The data also cannot tell if verbal or physical abuse are occurring during these stops. Due to these limitations, Dr. Meng hopes that his work encourages further research to find out what these stops are like for citizens.
“I think it is an important topic. Racial profiling affects our society, and it is especially harmful for minority communities,” said Dr. Meng. “It also wastes the police’s limited resources. Let’s assume they only have so many resources at a certain time. If they are stopping innocent people, that means there will be a lack of resources to target the real criminals among us.” Dr. Meng hopes as a result of his research, police will collect more data about racial profiling. The Toronto police have been faulted for not keeping clear records in regard to race. He also hopes there is greater monitoring of police behavior, such as the introduction of squad car cameras.