Exploring the Link between Crime and Socio-Economic Status in Ottawa and Saskatoon: A Small-Area Geographical Analysis
- Study # 1 - Ottawa Dissemination Areas
- Study # 2 - Saskatoon Neighbourhoods
- Study # 3 – A Comparison of Neighbourhoods in Ottawa and Saskatoon
Two types of data were collected and analyzed: criminal offence data obtained from the Ottawa Police Service (OPS) for 2001 and socio-economic data drawn from Statistics Canada's 2001 Census. Both the crime and census data were aggregated at the level of the dissemination area (DA). Dissemination areas were defined by Statistics Canada for the 2001 census and are small areas composed of one or more neighbouring city blocks, with a population of 400 to 700 persons. They are the smallest standard geographic areas for which all census data are disseminated. In 2001, there were approximately 1,200 DAs in Ottawa. Their small size makes them ideal for the geographic analysis of intra-urban patterns of criminal activity and socio-economic status.
Each criminal offence in 2001 was referenced to a geographic coordinate (longitude and latitude) by the OPS, recorded according to offence type (i.e. assault, break and enter, etc) and stored as a separate data point. For this project, the OPS supplied the point data aggregated to match the boundaries of Ottawa DAs, allowing the criminal offence data to be compared directly with census information. As shown in Table 4.1, the crime data were grouped into 6 principal offence types: "Total Offences", "Violent", "Major Property", "Minor Property", "Drugs" and "Disturbance/Other". The breakdown of types of offences in each group is listed in Table 4.2. The table shows that a total of 44,559 offences were included for analysis in the study. (Several offences, including traffic violations and certain federal statutes, were omitted). Minor property crimes accounted for more than half (54%) of all offences reported to police in Ottawa in 2001 with 'theft under $5000' being the most common incident within this category. Major property crimes represented 20% percent of the total with 'auto theft' the most prevalent. There were almost 7,000 violent offences in the city (16% of the total) with 'assault' comprising nearly two-thirds (63%) of the incidents in this group. The remaining offences were related to drugs (2% of the total) and 'disturbance/other' (8%). It is important to emphasize again that the crime data refers only to the location where the incident occurred but not the address of the offender, meaning that a high crime level in a neighbourhood, for instance, is not necessarily a reflection of the actions of the people residing there.
Table 4.1 displays the 26 socio-economic census variables used in the study. The objective was to establish a concise set of indicators, which reflect the socio-economic status and levels of disadvantage in Ottawa's communities. From the list, it is clear that unemployment, labour force participation, low income and low educational attainment are direct measures of disadvantage and have been used frequently in studies of urban social differentiation in North America and Europe. The recent immigrant, visible minority and lone-parent variables are not direct measures but are included because of the numerous problems that are associated with these groups in Canada including lower incomes, higher unemployment rates and subsequent dependency on social transfers. The three youth-related variables were included to highlight the potential problems related to crime and disadvantage in those communities with higher levels of young people who are unemployed and/or not attending school. Within the context of criminological theory, particularly social disorganization (Shaw and McKay) and the theory of deviant neighbourhoods (Stark), a number of mobility and housing related census variables were employed in the study including family status (single and married), residents who have moved during the past year, dwellings that are owned and rented, the age of housing, the type of dwelling (houses, row houses, apartments) and household density.
As shown in Table 4.1, the crime variables were calculated to reflect their rate per 1,000 population in each DA. A database was constructed consisting of 32 variables (6 criminal offences and 26 census indicators) for each of the 1187 DAs in Ottawa. (DAs with missing or suppressed census data were excluded from the study).
The Planning Branch of the City of Saskatoon has defined neighbourhood boundaries, which are displayed in Figure 7.1. The map highlights the nine communities designated as 'core neighbourhoods', seven of which are located on the west side of the South Saskatchewan River and include the Central Business District (CBD). Periodically, the Planning Branch publishes a report titled "Neighbourhood Profiles" in which detailed census, planning, real estate, school board and vehicle data is compiled for each of the city's neighbourhoods. The most recent edition (2003) was obtained for this study, which included data from the 2001 Census. In addition, 2003 criminal offence data was acquired from the Planning Unit of the Saskatoon Police Service (SPS). The SPS collects crime data by quadrant and fits this data to meet approximately the boundaries of each neighbourhood in the city. As a result, there may be some overlap of incidents into adjacent neighbourhoods. For this study, the crime, census and development/ planning data were compiled for 55 residential neighbourhoods. Due to low population numbers or missing values, industrial neighbourhoods were not included in the research.
Table 4.3 lists the 31 variables used in the study assembled into three categories. The crime variables were grouped into 5 main offence types: Total Offences, Violent, Major Property, Minor Property and Drugs. The sub-offences in each of these categories are listed in Table 4.4.
Table 4.3 also shows the 22 socio-economic census variables used in the study. Many have been employed in previous studies of crime and socio-economic status including population density, educational attainment, low-income, unemployment, lone-parent families, recent immigrants and housing characteristics. Saskatoon has a large and relatively disadvantaged Aboriginal population and since this group has been identified as 'at risk' with respect to crime (La Prairie 2000, Sacco and Kennedy, 2002; Mata, 2003) the decision was made to include this variable in the study. Finally, the third category is "Development, Planning and Vehicle Data" and includes variables denoting average home selling price, park space and vehicle use.
Table 4.5 shows a breakdown of types of criminal incidents in the Saskatoon CMA in 2003 as collected and presented by the Canadian Centre for Justice Statistics in their Uniform Crime Reporting (UCR) Survey. It shows that there were a total of 37,596 incidents in the urban area. Property crimes accounted for more than half (51%) of all incidents reported to police in Saskatoon in 2003 with 'theft under $5000' being the most common within this category. 'Break and Enters' are clearly a problem in the city with 5,028 incidents reported, comprising about 26% of all property crimes. There were over 4,100 violent offences in Saskatoon (11% of the total) with 'assault' comprising nearly three-quarters (74%) of the incidents in this group. The remaining incidents were related to 'Other Criminal Code Incidents' (35% of the total) with 'Mischief – property damage' being the most prevalent within this category. Finally, 'Federal Statutes', comprised mostly of drug offences, accounted for just 3% of all incidents.
As stated, one of the objectives of Study # 3 is to re-aggregate the dissemination area data used in the first Ottawa study to match the boundaries of the city's 50 neighbourhoods and compare these to Saskatoon's neighbourhoods. Table 4.6 lists the variables used in the analysis for the two cities at the neighbourhood level. As seen, the majority of the crime variables and many of the census variables were employed for both cities. A number of other variables were used for analysis in just one of the cities to reflect their unique characteristics. For example, two variables relating to immigration were included in the Ottawa analysis because immigration plays a greater role in the social geography of the city than it does in Saskatoon. Similarly, a variable measuring Aboriginal identity was included in the Saskatoon analysis as the city has a much larger number of these residents.
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