RECENT IMMIGRANTS AND UNDERCLASS
POPULATION IN CANADIAN CITIES

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Methodology - Project Design

The study's approach has been primarily qualitative and quantitative, exploring the Canada Census' 1996 and 2001 Current Population Survey. Spatial analysis of the census data was at CT level to identify spatial concentration of recent immigrants and underclass population in each city. Spatial statistical measures such as multiple regression was employed to examine spatial association between socio-economic conditions and recent immigrant attributes. Multiple regression assesses the relationship between recent immigrant population and socio-economic characteristics. Recent studies have shown that immigrants are more likely than non- immigrants to live in neighborhoods with high rates of poverty and that there is underclass of visible minorities, many of whom are recent immigrants, concentrated in racial enclaves of poverty (Semone K. and Laurel R. 2002).

Working with an enormous amount of data such census data requires not only appropriate spatial definition of aggregate areas represented by the data but also understanding how each data element is related to another in the dataset. Poverty as a social problem has many causes and results, and differentiating the causes from the results is important to working out the variables to include as independent parameters. While direct data elements can be used for some deductions, an appropriate and a more objective prediction relies on the spatial statistical analysis of these corporate data elements. In regards to the scope of this project however, more sensitive aggregate variables are considered to define poverty. All data values are collected at CT level for each Census Metropolitan Area (CMA). Data elements worked with are listed below.
Though government transfer payments may be considered as a result rather than a cause of poverty, its occurrence essentially reflects an impoverished population.


Conceptual idea        Introduction        Spatial Analysis        Conclusions

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