Exploring the Link between Crime and Socio-Economic Status in Ottawa and Saskatoon: A Small-Area Geographical Analysis
8. Study # 3 Findings: A Comparison of Neighbourhoods in Ottawa and Saskatoon
- 8.1 Principal Components Analysis
- 8.2 Multiple Regression Analysis
- 8.3 Geographic Patterns of Crime in Ottawa and Saskatoon’s Neighbourhoods
- 8.4 Discussion
8. Study # 3 Findings: A Comparison of Neighbourhoods in Ottawa and Saskatoon
8.1 Principal Components Analysis
As explained in Chapter 4, the dissemination area data for Ottawa (Study # 1) was re-aggregated to match the larger neighbourhood boundaries of the city. Again, the variables used in the analysis were transformed into Z-scores (Zi = (xi– x) / sdx ) in order to render the various indicators (crime, census and planning) statistically compatible. A principal components analysis (PCA) was performed on the Ottawa neighbourhood dataset to examine the degree of inter-relationship among the variables and to assess the association between crime and socio-economic/ neighbourhood characteristics (Tables 8.1 and 8.2). As seen in Table 8.1, the PCA produced a 6-component solution accounting for 86% of the total variance in the dataset. Similarly, the Saskatoon PCA (Table 7.2) produced a 6-component solution representing 84% of the total variance. These high variances indicate significant inter-correlation in the two datasets.
Table 8.3 shows the loadings on the first two components for each city and clearly indicates that in Ottawa there are separate axes for crime and neighbourhood characteristics. Component 1 loads highly on variables related to mobility and low-income while the loadings on Component 2 signify that the 5 crime variables are highly inter-correlated with one-another and significantly associated with only one of the 26 socio-economic variables - youth not attending school. However, Table 8.3 reveals that in Saskatoon there is a strong association between crime and neighbourhood characteristics. Component 1 loads highly and positively on violent and major property crimes and a number of socio-economic dimensions most notably Aboriginal residents, lone-parent families and low-income families. Component 2 highlights the association between minor property and drug offences in neighbourhoods with high-rise apartments and low rates of labour force participation.
8.2 Multiple Regression Analysis
A series of stepwise multiple regression analyses were performed on the Ottawa and Saskatoon datasets to examine the strength and intensity of the relationship between crime (the dependent variable) and socio-economic conditions (the independent variables). With respect to Ottawa's neighbourhooods (n=50), Table 8.4 provides a summary of the results by showing the coefficients of multiple determination (R2) and the significant independent variables for each regression model. It reveals several differences in the relationship between crime and socio-economic conditions in the two cities. In Ottawa, at the neighbourhood level, there is a moderate statistical association between the two dimensions with the crime variables having R2 values ranging from a low of 0.269 for drug offences to a high of 0.638 for major property offences. Several of the independent variables have significant beta coefficients. Most notably, the variables 'youth not attending school' and 'single' appear to be the best predictors of overall rates of crime as well as certain types of offences. The table shows that 'youth not attending school' is a significant independent variable for each of the 6 crime variables and is the only significant predictor of violent crime. In addition, the variable 'average household income' is a significant predictor of crime related to total offences, major property offences and disturbance/other offences.
By comparison, Table 8.5 shows that in Saskatoon there is a stronger association between crime and socio-economic conditions with each of the 5 regression analyses yielding relatively high R2 values (ranging from a low of 0.618 for minor property offences to a high of 0.726 for violent offences). The variable measuring government transfers, which reflects the level of social assistance received by residents, was found to be the most important predictor of overall crime in the city's neighbourhoods. Similar to the situation in Ottawa, the regression models for Saskatoon reveal that the variable denoting 'youth not attending school' is a significant predictor of overall crime as well as minor property and drug offences. However, as indicated in Study # 2, perhaps the most troubling finding to emerge from the Saskatoon analysis is the strong association between violent crime and Aboriginal people. The high R2 value (.726) and the high beta coefficient in the model suggest that Aboriginal people are most likely to be the victims in neighbourhoods with high rates of violent crime.
8.3 Geographic Patterns of Crime in Ottawa and Saskatoon's Neighbourhoods
ArcGIS was used to produce a series of maps showing the spatial distribution of crime and neighbourhood characteristics in Ottawa. As displayed in Figures 8.1 and 8.2, High Crime Areas (HCAs) are concentrated within the built-up central core and suburbs, with no HCAs visible in the outer and rural parts of the city. (HCAs are defined as neighbourhoods with crime rates in the 'High' and 'Highest' categories on the maps). However, it is also apparent that within the urban core, there is a fairly dispersed pattern of HCAs. The four communities with the 'Highest' crime rates (above 100 offences per 1,000 population) are the inner city neighbourhoods of Centre Town, Lower Town and Overbrook as well as Clementine located just west of Alta Vista. A number of neighbourhoods with 'High' crime rates are located within and immediately surrounding the inner city, including Vanier, Riverview/Hawthorne, Carleton Heights, Ottawa West and Dalhousie. Figure 8.1 also reveals a band of suburban neighbourhoods in the western part of the city with 'High' crime rates including Glencairn, Nepean West, Nepean North, Bells Corners and Pinecrest/Queensway. Figure 8.2 shows that violent HCAs in the city have a similar geographic pattern. The three neighbourhoods with the 'Highest' rates of violent offences are in the inner city – Vanier, Lower Town and Centre Town. HCAs in Ottawa exhibit certain socio-economic characteristics. Table 8.6 indicates that they have significantly higher population densities, greater proportions of visible minorities, single people, renters, residents living in high and low-rise apartments and people living in low-income.
As seen in Study # 2 of Saskatoon, HCAs are clustered in the core area. They are particularly visible in the inner city on the west side of the South Saskatchewan River and also correspond with socio-economically disadvantaged neighbourhoods. A distinguishing geographic feature of Saskatoon is a tight clustering of violent HCAs all located in the west side of the city with most having high proportions of Aboriginal residents, including Pleasant Hill, Riversdale, Confederation Suburban Centre and Meadowgreen. However, as was emphasized in the Saskatoon study, only three of the city's neighbourhoods have Aboriginal populations greater than 30% and none have more than 50%. This fact suggests that ethnic segregation is not a major feature of Saskatoon and that issues of crime and victimization effect a wider segment of the city's population. Several of the neighbourhood characteristics of HCAs are similar to those found in Ottawa including larger proportions of singles, renters and low-income residents. One important difference, however, is the presence of older and lower quality housing in Saskatoon's HCAs, particularly those in the inner city.
8.4 Discussion
This study provided a brief comparison of crime and neighbourhood characteristics in Ottawa and Saskatoon. It found that Saskatoon has a substantially higher rate of crime than Ottawa and, overall, has a higher incidence of socio-economic disadvantage. The initial Ottawa analysis (Study # 1) employed data at the level of the dissemination area and found that there is a weak association between crime and socio-economic status in the city. The re-analysis of the data at the neighbourhood level in Ottawa demonstrated that a change in geography does have an impact on the statistical 'strength' of this relationship. Several indicators were found to have a significant effect on crime levels in the city's neighbourhoods including higher proportions of single people and youth not attending school as well as lower average household incomes. The geographic analysis showed a fairly dispersed pattern of High Crime Areas (HCAs) within Ottawa's urban core including a noticeable presence in several of the city's western suburban neighbourhoods.
By comparison, in Saskatoon, there appears to be a stronger and more direct link between crime and socio-economically disadvantaged neighbourhoods, particularly those with higher proportions of low-income families and Aboriginal residents. Saskatoon's neighbourhoods, on average, have much higher rates of crime. In addition, HCAs (particularly violent HCAs) are located primarily in the inner city with very few in suburban neighbourhoods.
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