Patterns of Crime in Canadian Cities :  A Multivariate Statistical Analysis

Section 6. Crime Profiles for Different City Sizes


6. Crime Profiles for Different City Sizes

One common perception is that cities with different population sizes demonstrate different crime patterns. In order to test whether this is supported by objective data, the data (4 factor scores for the 600 cities) were again put to a discriminant analysis. This time, instead of provinces or geographical regions, the initial classification into groups was based on city size. Different classifications by city sizes were tested. It was decided in the end that the customary boundaries of 100,000, 50,000 and 10,000 would be used as the 100,000 population limit is used by Statistics Canada to classify Census Metropolitan Areas (CMAs).

The 600 cities were then assigned into 4 groups by their population.

Grouping by City Size Classes
Size 1 – Large cities (100,000 and over) 38 cities
Size 2 – Medium cities (50,000 to 100,000) 44 cities
Size 3 – Small cities (10,000 to 50,000) 185 cities
Size 4 – Towns (under 10,000) 333 cities

Table 6 shows the results of the discriminant analysis based on city size classes.

  • Out of the 38 large cities (row 1 in the table), 17 cities or 45% had crime patterns similar to the profile for large cities and were classified into their original group; 9 cities or 24% were similar to the profile for medium cities; 12 cities or 32% were similar to the profile for small cities; 0 cities or 0% were similar to the profile for towns.
  • Out of the 44 medium cities, 11 cities or 25% had crime patterns similar to the profile for medium cities and were classified into their original group; 15 cities or 34% were similar to the profile for large cities; 15 cities or 34% were similar to the profile for small cities; 3 cities or 7% were similar to the profile for towns.
  • Out of the 185 small cities, 90 cities or 49% had crime patterns similar to the profile for small cities and were classified into their original group; 26 cities or 14% were similar to the profile for large cities; 21 cities or 11% were similar to the profile for medium cities; 48 cities or 26% were similar to the profile for towns.
  • Out of the 333 towns, 226 cities or 68% had crime patterns similar to the profile for towns and were classified into their original group; 16 cities or 5% were similar to the profile for large cities; 15 cities or 5% were similar to the profile for medium cities; 76 cities or 23% were similar to the profile for small cities.
  • Over all, 344 or 57% were classified correctly, that is, classified into their original group. This implies that the differences among city size crime profiles are slightly more distinct than the regional differences (where 53% were classified correctly). A complete list of cities that require reclassification is in Appendix 5.
Table 6. Results of Discriminant Analysis of 4 City Size Classes
From Size Class Number and Percent of Cities Classified Into City Size Class
Large cities Medium cities Small cities Towns TOTAL
Large cities
(100,000 & over)
17 9 12 0 38
45% 24% 32% 0% 100%
Medium cities
(50,000 to 100,000)
15 11 15 3 44
34% 25% 34% 7% 100%
Small cities
(10,000 to 50,000)
26 21 90 48 185
14% 11% 49% 26% 100%
Towns
(under 10,000)
16 15 76 226 333
5% 5% 23% 68% 100%
TOTAL 74 56 193 277 600
12% 9% 32% 46% 100%

NOTE: The shaded boxes with bold letters represent the cities classified correctly.

Table 7 shows the representative crime profiles of the 4 city size classes, in terms of average factor scores of the 4 crime components.

  • Large cities have slightly below average minor crimes, very low violent crimes, very high major property crimes, very high moral crimes.
  • Medium cities have average minor crimes, low violent crimes, high major property crimes, high moral offences.
  • Small cities have average minor crimes, slightly below average violent crimes, slightly above average major property crimes, average moral offences.
  • Towns have average minor crimes, above average violent crimes, below average major property crimes, slightly below average moral offences.
Table 7. Average Factor Scores of the 4 City Size Classes
Region Comp. 1 Comp. 2 Comp. 3 Comp. 4
Minor crimes Violent crimes Major property crimes Moral offences
Large cities -0.17 -0.67 0.71 0.54
Medium cities -0.08 -0.54 0.43 0.38
Small cities -0.07 -0.21 0.12 0.03
Towns 0.07 0.27 -0.21 -0.13

The above results show that contrary to popular belief, violent crime rates are actually a greater problem in small towns than in large cities. This counter-intuitive conclusion is actually supported by the higher violent crime rates (with the exception of homicide, robbery, and abduction) reported in towns (see Appendix 6 for the average crime rates by city size classes). It should be noted, however, that while the absolute numbers of violent crimes may be high in large cities, the rates are low because of the large population base.

The results also show that how adjacent cities may demonstrate very different crime patterns. For example, Richmond, a suburb of Vancouver (a large city with a population of 164,000) has a crime pattern similar to the crime profile for medium cities. On the other hand, Delta, another suburb of Vancouver (a large city with a population of 101,000) has a crime pattern similar to the crime profile for small cities (see actual crime rates of these cities in Appendix 1).

Crime Patterns of Two Sample Large Cities in British Columbia
Component Richmond, BC Delta, BC
Factor Score Percentile Factor Score Percentile
1 Minor crimes 0.03 62 0.08 67
2 Violent crimes -0.45 26 -0.55 13
3 Major property crimes 0.68 81 0.19 69
4 Moral offences 0.16 71 -0.20 46
Crime Profile Medium City Small City

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