Patterns of Crime in Canadian Cities :  A Multivariate Statistical Analysis

Section 7. Summary and Policy Implications


7. Summary and Policy Implications

In this study, factor analysis was successfully applied to objectively derive 4 meaningful crime components by grouping together highly correlated offences. The factor scores associated with the 4 components could be used as crime indices to summarize the rates of 25 offence categories. In this way, the factor scores provided a more concise and meaningful way to describe the crime patterns of all 600 cities than the traditional crime rates.

The discriminant analysis showed that crime patterns in the four Atlantic provinces and the three Prairie provinces are generally similar while the crime patterns in the three larger provinces (Ontario, Quebec, British Columbia) are distinct from other provinces. In terms of city size, the discriminant analysis again showed that crime patterns do vary by population level (see Table 8). While the analysis was only moderately successful in deriving the crime profiles (with slightly over half of the cities correctly classified) for the 4 geographical regions and for the 4 city size classes, the results were useful in showing whether individual cities resemble other cities in the same group or resemble cities in other groups.

Table 8. Summary of Crimes by the Two Classification Schemes
Classification Scheme Component 1 Component 2 Component 3 Component 4
Minor crimes Violent crimes Major property crimes Moral offences
Geographical Regions high in British Columbia; low in Quebec high in Atlantic/ Prairies; low in British Columbia very high in British Columbia; low in Ontario high in British Columbia & Ontario
City Size Classes minor differentiation high in towns; low in large & medium cities very high in large cities; low in towns increase with city sizes

This kind of information is useful for government, individual police departments and individual communities to better understand their crime patterns and to use this information to develop their own crime control and prevention strategies. First, cities may choose to focus their efforts on those crimes problematic to its own area as indicated by high crime indices, that is, high factor scores for specific crime components. Second, the development of regional and city size crime profiles shows how the crime pattern in a particular city may or may not be similar to other cities in its original grouping. Adopting successful crime prevention programs used by cities with the same crime profile may be an effective strategy in designing local programs. For example, a city with a large population may in fact have a crime pattern similar to small cities and crime prevention programs suitable for other large cities may not be the optimal choice. It is therefore appropriate to consider organizing roundtables among different layers of police to discuss common strategies in view of the crime similarities and dissimilarities found.

In terms of a national strategy for crime prevention, it is important to understand how crime problem varies from region to region and at the same time varies from city to city. As a result, very different crime prevention strategies should be employed in different specific situations.

This study employs various kinds of multivariate statistical methods to describe crime patterns of individual cities. The same kind of methodology may also be applied to other aspects of crime. The question of stability of the crime components may be addressed by analyzing data from different years. Such analysis will also be useful to detect crime trends for individual cities. Furthermore, as some crime prevention activities are directed towards reducing youth crime, the methodology in this study can be applied to data on the number of youth charged by the police. The results will be useful to pinpoint the type of youth crime problems in individual cities.