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Were further
research to be conducted on this topic, a primary factor of
consideration could
be the proportion of child residents by neighborhood (using
Dissemination Areas
or Census Tracts as the areal unit of analysis, since this would be
Census data
from Statistics Canada). While not a consideration in any of the
Megan’s Law
legislation in the United States, this would appear to be a base
assumption
underlying this type of logic: to keep convicted child sex offenders as
far
away as possible from their prime targets (i.e. children), prohibit
them from
living in communities with high proportions of young residents. This
data could
be found through Statistics Canada and those areas with high
proportions of
children could either be buffered or removed from the residential layer
altogether. Again, this further restriction may be next to impossible
to
enforce, however.
Another more
technical form future research could take would be to use a different
program
from ArcGIS altogether, or at the least a different tool than
ModelBuilder
within a GIS package. We ran into numerous difficulties executing our
model,
and programs better equipped to deal with this type of analysis could
have been
employed more advantageously (i.e. a programming language such as
Python). In
terms of the breadth and scope of this course in GIScience, however,
the use of
ArcGIS and its extensions was necessary – also, learning an entirely
new
software program or programming language didn’t appear to be feasible
within
the timeframe of this project.
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