It does seem to have turned into Police Month here on Northern Economist given that the first four February posts have been reposting of a series I did for the Fraser Institute Blog on policing in Ontario. Well, to add to that, some charts, and statistics on policing in the five major northern Ontario cities: Thunder Bay, Timmins, Greater Sudbury, Sault Ste. Marie, and North Bay. The data is from Statistics Canada - Table 35100077 - Police personnel and selected crime statistics, municipal police services, annually. These provide an overview of police resources in these cities and perhaps the best way to start off is with an overview of crime.
Figure 1 plots the Crime Severity Index for these five cities over the period from 2000 to 2021. Crime Severity was on a downswing in all five of these cities from about 2010 to 2015 and since then appears to have increased. Between 2015 and 2021, crime severity increases 19 percent in Thunder Bay, 61 percent in Timmins, 78 percent in Sault Ste. Marie, 48 percent in Sudbury and 67 percent in North Bay. While in 2010, crime severity was highest in Thunder Bay, by 2021 Thunder Bay’s crime severity had been surpassed by Timmins, Sault Ste. Marie, and North Bay.
Figure 2 plots the number of municipal police officers for each of these five cities and the largest forces are in Sudbury, followed by Thunder Bay, Sault Ste. Marie, North Bay and then Timmins. In 2021, Sudbury reported 257 officers while Thunder Bay had 238, the Sault 136, North Bay 98, and Timmins 81. Between 2000 and 2021, all of these police forces grew but since 2015 the Timmins force has actually shrunk 5 percent while the Sault and Sudbury remained flat and Thunder Bay and North Bay grew 7 percent each.
Of course, police forces also employ civilian and other personnel to support the officers and Figure 3 plots the total number of these employees for the 2000 to 2021 period also. Relative to 2015, these have increased though after a lengthy prior period of staying flat. However, the largest increases appear to characterize Sudbury and the Sault. Between 2015 and 2021 the number of civilian and other personnel employed by police forces grew 10 percent for each of Thunder Bay and Timmins, 24 percent in North Bay, 42 percent in the Sault and 43 percent in Greater Sudbury. The ratios of supporting civilian staff to police officers vary across these communities. For example, Thunder Bay has 1 civilian staffer per 2.4 police officers while Sudbury has 1 civilian staffer per 1.6 officers.
Another comparison is provided in Figure 4 for police officers adjusted for population, that is police officers per 100,000 population and suggests an overall long-term increase in all of these communities from 2000 to 2021. The most officers per 100,000 population in 2021 is in Thunder Bay at 200 per 100,000 followed by Timmins at 192, then the Sault at 177, North Bay at 170 and Greater Sudbury at 152. Since 2015, the number of officers per 100,000 has grown 5 percent in Thunder Bay, 6 percent in North Bay, stayed flat in the Sault, and actually declined by 2 percent in each of Timmins and Sudbury.
Finally, what is the relationship between policing and crime in these five northern Ontario cities. Well, figures 5 and 6 plot two relationships. Figure 5 plots the Crime Severity Index against police officers per 100,000 and puts in a linear trend and it shows a positive correlation between crime severity and police officers per 100,000 population with a fair amount of variation around the trend. In terms of interpreting the result, it could mean that communities with more crime severity need more police officers, or it could be that communities with more police officers are able to report more crimes. However, if one wants a better indicator of effectiveness, then figure 6 may be more helpful. It plots the relationship between weighted clearance rates and the number of police officers per 100,000. Clearance rates are the proportion of crimes that are cleared, that is a charge laid. A weighted clearance rate attaches a higher weight to the clearance of more serious crimes such as homicides. The chart shows a positive correlation between clearance rates and the number of officers per 100,000 also with a fair amount of variation around the trend.
So, what is the takeaway from all this? First, policing resources and crime severity vary a great deal even within these five communities. Some of them have seen substantial surges in crime severity since 2015. Second, police forces not only employ police officers, but they have substantial civilian staff also and some of them have more support staff than others. An important question is if these additional staff are able to free up officers for more police work and how effective their supporting roles are, but this question is difficult to assess without a lot more analysis with more confounding factors considered. Third, as limited an analysis as it is, having more police officers per 100,000 is correlated with higher clearance rates though how many convictions ultimately result is also something that requires more data.
One wonders if any of these municipalities have actually
done any analysis of the data they must obviously have that examines their
staffing and the relationship between staffing, crime rates and crime severity and
clearance rates. One imagines that all of these municipalities have in place staff with statistics training to do data analytics that can then be used to assess their own needs and performance as well as make the case for resources when the need. I am actually surprised there was not more mention of things like "more officers improve clearance rates" in much of the public discussion reported on police requests for hiring. Or, for that matter that large proportions of many police forces are nearing retirement age and you need to plan for replacements. On the other hand, I may simply have an over active imagination and assume a lot about the abilities of public sector entities to make effective cases on their own behalf.