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A Social and Spatial Analysis of Firearm Related Incidents in Toronto
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<p>The overall objective of this paper is to determine the location of spatio-temporal clustering of Firearm Related Incidents (FRI) in the City of Toronto between 2014-2018, to determine specific demographic, economic and social variables that would most likely be impacted by FRI violence and explore potential locations to host support groups for populations disproportionally impacted by FRI. Utilizing PCA/factor analysis and a grouping analysis (K-Means) was done as an attempt to minimize the presence of ecological fallacy and reduce the impact of spatial stigma typically associated to subgroups of the population historically impacted by FRI. A regression model was done to test the validity of the grouping analysis and finally a location-allocation model was produced to identify potential support centre locations. Findings revealed that FRI in Toronto rose between 2014-2017 but decreased in 2018. There is spatial auto-correlation occurring throughout all years and areas historically impacted see a rise in FRI as years progress. Findings also revealed that variables for low educational attainment, low income, high visible minority status, lone parents and those between the ages of 0-19 were more likely to encounter FRI. A total of 21 potential locations were identified in a way to alleviate the side effects of FRI occurring in identified areas.</p>
Title: A Social and Spatial Analysis of Firearm Related Incidents in Toronto
Description:
<p>The overall objective of this paper is to determine the location of spatio-temporal clustering of Firearm Related Incidents (FRI) in the City of Toronto between 2014-2018, to determine specific demographic, economic and social variables that would most likely be impacted by FRI violence and explore potential locations to host support groups for populations disproportionally impacted by FRI.
Utilizing PCA/factor analysis and a grouping analysis (K-Means) was done as an attempt to minimize the presence of ecological fallacy and reduce the impact of spatial stigma typically associated to subgroups of the population historically impacted by FRI.
A regression model was done to test the validity of the grouping analysis and finally a location-allocation model was produced to identify potential support centre locations.
Findings revealed that FRI in Toronto rose between 2014-2017 but decreased in 2018.
There is spatial auto-correlation occurring throughout all years and areas historically impacted see a rise in FRI as years progress.
Findings also revealed that variables for low educational attainment, low income, high visible minority status, lone parents and those between the ages of 0-19 were more likely to encounter FRI.
A total of 21 potential locations were identified in a way to alleviate the side effects of FRI occurring in identified areas.
</p>.
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