By Rebecca Wissink
When shopping for a home you have a list of needs: a certain number of bedrooms and bathrooms, perhaps proximity to infrastructure like transit, hospitals, or good schools, and maybe you’ve considered the safety of the neighbourhood. If you’re a newcomer to this province or town, you might be especially concerned about the neighborhood you are house hunting in given you don’t know the city as well as a local. Which begs the question, why don’t real estate listings have crime scores or ratings? MLS listings can have walk-scores, which I’ve written about for Ross Pavl. And every MLS listing has a tab called “Statistics” that will show you demographic information about the neighbourhood, like the average age of the residents, average household income, and how many people have children or are unemployed. But should MLS listings have crime scores? Would that bias shoppers away from certain areas, devaluing properties unfairly? Most likely. In contrast, this information could also be used to challenge inaccurate neighbourhood reputations. In a bigger city like Calgary, you can get what amounts to a crime score for a neighbourhood, even if the MLS listing doesn’t offer that information. This article gives you a step-by-step guide on how to use the City of Calgary’s crime map, along with some cautions about how to interpret the data.
Centering the city’s crime map page is a colour coded map of the city as seen in Figure 1 below. On the right of the map is the colour coded legend for crime statistics as seen in Figure 2 below. The darker the colour, the more general crime.
Figure 1. City of Calgary Crime Map (Source: City of Calgary)
Figure 2. The Colour Coding Legend for the City of Calgary's Crime Map (Source: City of Calgary)
Figure 3. Filters for the City of Calgary Crime Map (Source: City of Calgary)
To the right of the map and legend are filters, as seen in Figure 3 above, which allows the user to get detailed information on each community by using the drop-down menu to narrow the search. One can choose to focus on any of nine crime types, a year between 2017 –2022, any month of the year, and the neighbourhood. You can also select multiple values in each drop-down menu. For example, if you want to know what the general crime level was across the city last summer, you can select July and August for 2021, and you’ll see that Beltline experienced 333 crimes, which was the highest of any neighbourhood. Once you have specified some values, you simply hover your cursor over the highlighted area of the map, and it shows the number of incidents. If you’re trying to work through this, you'll need to scroll to the bottom of each drop-down menu and click “apply.” If you want to change a value, click the drop-down arrow, and then click on the “X” to the right under “selected values,” which is at the top. This will clear your choices once you click “apply” at the bottom. Lastly, in the bottom centre third of your screen under the map you can see a breakdown of the most recent crimes by sector of the city, community, type of crime, the number of times that crime was committed in that month and year, and perhaps most importantly for context, you get a resident count for that community. Figure 4 below is an example. The resident count can be found in the lower half of your screen in the fifth column from the left.
Figure 4. Example Table from the City of Calgary's Crime Map (Source: City of Calgary)
Why would a resident count be important for analyzing data? First, it is required for the math equation that gives a per-capita crime rate as a percentage. Secondly, as a researcher, I caution you that data needs to be contextualized, and the city’s crime map has been neither contextualized nor analyzed. Data without human analysis, or even a per-capita crime rate, can be misunderstood. This website does a fantastic job of supplying raw data given you can isolate data by multiple metrics, and is a tool that offers home buyers one more piece of information about prospective neighbourhoods. But the data lacks analysis. There is another website you can use that offers a “score” based on letter grades, suggesting analysis has occurred, but it only differentiates between violent and property crimes.
As a potential home buyer, you are likely most concerned about break and enter – dwelling. If you want to use this crime map as a tool to understand a neighbourhood, you also need to consider the type of housing that dominates the area. Although Beltline has the highest colour code ranking for overall crime, it does not have the highest number of break and enters. Tuscany (19,884 residents), Signal Hill (13,395 residents), Edgemont (15,395 residents), and Panorama Hills (25,710 residents), all have a greater number of break and enters than Beltline. This is likely because Beltline is dominated by multi-family units which are harder to access than the single-family dwellings found in the suburbs. One has a lot more neighbours watching out for suspicious activity in a multi-family unit than the single-family homes in the suburbs.
Further contextualization comes when considering why people are in the area. While Beltline and the Downtown Commercial Core appear to have the highest crime rates in Calgary, they also have the highest number of people moving in and out of that area for work or play. These areas host two significant spots in Calgary for nightlife and eating out, and Beltline is home to the Stampede grounds and the Saddledome. This means a lot of people who don’t live in the neighbourhood are visiting it, and some are consuming alcohol, which acts as a disinhibitor and can be a precursor to some criminal behaviour. And the Downtown Commercial Core’s daytime population swells exponentially given so many workers move in and out of the area daily. As of the 2016 Census, there were approximately 137,000 jobs within Calgary’s downtown core. The number you see on the screen is a count, and it has not considered whether the crime was committed by or against a resident. Only that the crime was committed inside that neighbourhood’s boundaries. Even knowing the time of day or night that a crime occurred in the Downtown Commercial Core would provide more context to help understand the trends in the area.
Lastly, you want to consider the type of crime, and the context in which it might occur when considering raw data. For example, a street robbery is classified separately from assault or violence other on the map. Street robberies aren’t particularly common in Calgary, but Beltline and the Downtown Commercial Core have the most severe colour code for this type of crime. Some of the crime in Beltline likely occurs in the context of weekend drinking, hockey games, or Stampede, given 9% of its crimes are assault or violence other (2,331/25,129 people) and we know the socio-cultural amenities of the area. And 23% of the crimes in the Downtown Commercial Core were thefts from vehicles (1,995/8,683) which makes sense given how many people commute to work and park for the day. However, 26% of the crimes in the Downtown Commerical Core were also assault or violence other (2,239/8,683). While the actual crime count appears to be the same between Beltline and the Downtown Commercial Core, the Downtown has only about one-third the population of Beltline, making it far more “dangerous” in terms of violent crimes. I can’t prove with the data as it is presented that the high crime rate in Beltline and Downtown are directly caused by people coming into the area to party and consume alcohol, but it’s a logical conclusion to me. I can also surmise given the numbers I’ve presented that as a resident of Beltline, you aren’t likely in a whole lot of danger of crime, despite its colour code.
Let’s look at some other neighbourhoods to figure out their overall per capita crime rate which further shows the need to contextualize data. Panorama Hills in the North has a population count of 25,710 people and is labelled with a moderate colour code on the city’s map, yet has an extremely small number of total incidents (1,150 = 4% per capita). In contrast, Seton in the South-East has an exceptionally low population count of 1,134 persons and is labelled with a low-moderate colour code because it only had 337 incidents but this is a higher rate of crime per capita (30%). Dividing the number of crimes by resident count shows that Seton has a much higher crime rate than Panorama Hills and should not be given a lower colour code on the map. Using this math equation, Beltline, with a resident count of 25,129, and 8,727 crimes, has a 9% crime rate per-capita, while the Downtown Commercial Core, with a lower resident count of 8,683, and 6,057 crimes, has a significantly higher per-capita crime rate at 70%. According to the raw data and the colour coding system, Beltline and the Downtown Commercial Core have the same rate of crime. But the math shows that the Downtown Commercial Core has a significantly higher likelihood of crime based on its much lower resident population, which we’ve already noted isn’t representative of the number of people actually in the area Monday-Friday, 9-5.
Further if we only look at the two violent crimes of assault or violence other, Bowness, with a population count of 11,150 (which is higher than the Downtown Commercial Core), had 621 incidents and has a moderate-high colour code on the map, yet has a 6% per-capita crime rate for these two offences. In contrast, Forest Lawn (population 7,814) also has a moderate-high colour code with 787 violent crimes, but has a 10% per-capita crime rate. Saddle Ridge has a moderate colour code with 270 violent crimes (population 22,321 = 1%), and Sunalta, which is directly west of Beltline and the Downtown Commercial Core, was also given a moderate colour code with 237 violent crimes (population 3,239 = 7%). It is misleading to use a colour-coded system that labels Bowness with a more “severe” colour ranking than Sunalta when, per-capita, Sunalta records more violent crime by 1%.
There are other potential flaws with this type of data, particularly from a sociological perspective. This data may be derived, in part, from algorithmic (see Note 1) predictive policing technology (see Note 2), which is problematic. In short, algorithmic or predictive policing uses historical data to focus on either persons that are identified as more likely to commit crime, or geography that is more likely to experience crime. Generally, as arrests and complaints are fed into the computer system, the algorithm tries to find correlations and predict where crime will occur next, or who will commit the crime. When resources are tight, the focus goes to policing the areas or the people that the algorithm has determined pose or are at risk. However, the critique of this practice is that what we shine a spotlight on, we see with more clarity. If the police are patrolling a neighbourhood excessively, they will find crime there more often, while crime will go undetected in other areas of the city because the police aren’t there to see it.
With so much to consider when shopping for a home, it’s always best to use a licensed Realtor® who knows the local neighbourhoods inside and out and can access information not easily available to the public. If you have any questions about neighbourhood crime rates in the context of real estate, please contact an experienced Ross Pavl ELITE Real Estate Group Realtor® today.
Note 1 – an algorithm is simply computer coding that dictates - “if this, then that.” Your Netflix and Spotify accounts run on algorithms. Whenever you watch or listen to something, the algorithm notes, if you like this show/movie/song, then you’ll probably like that show/movie/song, which is how it makes its recommendations.
Note 2 - As of September 2020, Calgary Police Services were known to use “a product [that] integrate[s] various data sources for analysis, but not for the software’s algorithmic and predictive policing capabilities (such as integrating social media content, email and telecommunications information, financial records, and credit history).” The software Calgary Police Services employs has the capability for predictive policing, although it is a person-focused program, rather than a geographically focused program. Calgary Police Service appears to use the program primarily for facial recognition and social network analysis.
Cover image via creative commons courtesy of kevin dooley