Discussion

This report has presented information from the second Statistics Canada study on the spatial distribution of crime in a Canadian city using a combination of statistical analyses and crime mapping based on Geographic Information System (GIS) technology. Results from the examination of Montréal data are in agreement with those from other studies in Canada and abroad indicating that crime is not randomly distributed across cities, but is concentrated in certain neighbourhoods where demographic, socio-economic and urban land use factors have an impact.

Similar to what the Winnipeg and Regina studies have shown, there is, in Montréal, a concentration of crime in a limited number of neighbourhoods. However, this concentration exhibits a different pattern from that observed in the Western Canadian cities. Property offences are essentially concentrated in neighbourhoods in the city centre, while violent offences are distributed among a number of hot spots.

Bivariate results show significant differences with respect to some characteristics when neighbourhoods with high crime rates are compared with those with low crime rates. The results suggest that crime is more prevalent in neighbourhoods where residents have less access to social and economic resources. These neighbourhoods are characterized by a population that is economically more disadvantaged and includes a lower proportion of highly educated people. These neighbourhoods are also more likely to have a larger number of single persons, lone-parent families and recent immigrants. They also exhibit greater residential instability, a smaller number of owner-occupants and a larger proportion of the population that spends more than 30% of their budget on housing. More commercial and multi-family land use is also seen in neighbourhoods where the highest rates are reported. Nevertheless, it must be remembered that these are crime rates that are measured at the neighbourhood level and not the delinquency rates of their residents. It is therefore important not to make generalisations.

This study has shown that many of these individual factors are closely related. These are, for example, the proportion of the neighbourhood's residents in a low income household, which is in close statistical association with the unemployment rate; government transfers; the proportion of tenants in a neighbourhood; and the proportion of single-parent families and recent immigrants in a neighbourhood. Thus, when the variables were held constant through the use of a multivariate technique, a few key factors were shown to be most highly related to both property and violent crime rates. These variables suggest that there are unique dynamics in the study area, the Island of Montréal.

After taking these other variables into account and screening out the effect of the location of the neighbourhood, it becomes clear that the proportion of persons with a university degree stands out for its greater power to explain the variation in violent crime rates: the larger the proportion of persons with a degree in a neighbourhood, the lower the level of violent crime. At first glance, the considerable proportion of highly educated persons appears to offer some protection against violent crime at the neighbourhood level, whereas low income and single status contribute the most to explaining high violent crime rates in neighbourhoods. The type of land use also contributes to the explanation of crime; an especially important factor is residential zoning (multi-family and single-family) and, to a lesser extent, commercial zoning.

The results for property crime are somewhat different. Commercial zoning is the factor that offers the greatest explanatory power for the variation in property crime rates. Low income and single status also play a role in explaining crime at the neighbourhood level. When all other variables are held constant, bar density is found to be a significant factor associated with property crime, whereas this was not the case for violent crime.

The research results obtained at the neighbourhood level in Montréal support Sampson and Raudenbush's (1999) hypothesis, which proposes that violent crime varies according to the level of social capital or related concepts such as collective efficacy. Social capital is defined as social interactions and standards which facilitate decisions toward formal and informal collective measures in the interest of individuals and the community. Several characteristics of the human capital of residents in a neighbourhood, such as education, training and socio-economic status, are key to the development of social capital and better collective efficacy.

Compared to Winnipeg or Regina, Montréal has several separate clusters of low-income neighbourhoods (e.g., Lachine, Sud-Ouest, Hochelaga–Maisonneuve, Côte-des-Neiges, Parc–Extension, Montréal-Nord) surrounding a relatively well-off city centre. With the revitalisation of low income neighbourhoods (e.g., Plateau Mont-Royal, Vieux-Montréal), low income intensity in the urban core is being reduced (Heisz 2005). There would thus appear to be several hot spots of violent crime with less of a concentration than seen in the Winnipeg and Regina studies. The most at risk demographic groups facing low income also differ regionally. In the Montréal region, recent immigrants and lone-parent families are the most at risk, representing 14 % and 19 % respectively of the low income population in 2000.  These same demographic groups represented 6% and 27% respectively of the low income population in Winnipeg, and 2% and 27% in Regina.  Compared to Montréal (0.5%), a higher proportion of the low income population can be found among aboriginals in Winnipeg (24 %) and Regina (26 %) (Heisz and McLeod, 2004). 

In Montréal, neighbourhoods with the highest proportion of lone-parent families, recent immigrants and single status seem to have a lower collective efficacy. The low income situation of these demographic groups, which is associated with areas having higher residential mobility and the existence of more commercial and multi-dwelling zoning, decreases the informal social control function. According to Sampson and Raudenbush (1999), residential stability has long been considered a key element in strong urban social organization, and its absence is seen as a lost opportunity for residents to contribute to the community. Clifford and Hope (2004) contend that measures to encourage the residential revitalization of neighbourhoods serve to halt and reverse social disorganization and help maintain a diverse population that is more able to take on a surveillance role.

As regards the protective effect against property crime afforded by a higher proportion of visible minorities in a neighbourhood, the results of the 2004 General Social Survey can shed light on this relationship. The protective effect of this variable appears to be due to the economic disadvantage faced by visible minorities rather than to any real advantage. The fact is that the risks of victimization of households increase with household income (Gannon and Mihorean 2005). Hou and Picot (2003), who studied visible minority enclaves and labour market outcomes of immigrants in large Canadian cities, found that in Montréal neighbourhoods where blacks had a dominant presence, the proportions of unemployed and low income persons were also very high. Moreover, their analysis showed a significant association between exposure to members of the same group and lower income among black immigrants, even when the effects of low income in the neighbourhood were taken into account. Sampson and Raudenbush (1999) stressed that the relationship between disadvantage and crime is so close that other "symptoms" that characterize high crime neighbourhoods actually result from socio-economic disadvantage.

The study also showed that persons charged in criminal incidents that occurred in 2001 came primarily from the Island of Montréal. They came from a larger number of neighbourhoods in the case of violent incidents and were less concentrated than in the case of property crimes. Descriptive analyses of the median distance travelled by charged persons led to the finding that distances travelled vary depending on the type of offence, the age of the persons charged and their relationship with the victim. Overall, persons charged in violent incidents travelled less (0.9 km) than those charged in property incidents (4 km). Other research papers have also shown that persons accused of violent offences travel shorter distances than those accused of property crimes (LeBeau 1987; Turner 1969). This study also found that distances travelled vary depending on the age of the persons charged. The youngest travel the most in violent incidents and the least in incidents involving property. A number of foreign studies have produced similar results (Groff and McEwen 2005; Wiles and Costello 2000; Chapin and Brazil 1969; Harries 1999). The median distance travelled also varies according to the closeness of the relationship between the person charged and the victim. Charged persons who know their victim travel little, while those who do not cover a greater distance and converge toward the city centre.

Results from the Montréal study support British research findings indicating that most offender movements are relatively short, and that travel associated with crime is driven by opportunities presenting themselves during daily activities rather than plans to offend (Felson and Clark 1998; Wiles and Costello 2000). Offenders and their targets vary according to the initial reason for travelling—or not travelling, in the case of spousal violence. In this regard, trips initiated for work, school or recreation offer specific opportunities for crime (Felson and Clark 1998). The longer median travel distances recorded for auto theft incidents seem to be related to a more organized criminal effort.

Opportunities for crime increase when neighbourhood land use patterns are conducive to crime (Hayslett-McCall 2002). Land uses that have been associated with crime include mixed patterns of residential, commercial, industrial and vacant lands within neighbourhoods, as well as the presence of particular establishments, such as shopping malls and bars. Land use patterns can impact crime by inhibiting the social control or guardianship capacity of residents in a neighbourhood or by being a focal point for particular types of activities (e.g., consuming alcohol at a bar, selling or using drugs in abandoned structures) (Hayslett-McCall 2002).