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A Quantitative Look at Crime Dexter Training Ground - 1642 violations Furthermore, one can also determine which crime types are most prevalent in regards to their contribution to total crime (when aggregating crime in all the park regions). The last line of the table informs the following hierarchy, showing the crime types from greatest to least percentage of total crime: Property Violations - 35% Interestingly, the crime patterns around each of
the parks mirror this hierarchy. In each case, the different crime-types
comprise very similar percentages of total crime. For example, for all
the parks, non-violent criminal violations comprise between 22% and 25%
of the total crime. Firstly, when looking at where the case study parks are located in relation to crime hotspots, it is clear that none of them are located in any of these major hotspots. Fargnoli Park - as expected, it being the park situated in a stable neighborhood with generally low crime - is nowhere near to crime clusters. Sackett Street is also located in a low-crime area, unlike the regions further north of it in the rest of the Elmwood neighborhood. Billy Taylor Park, Dexter Training Ground, and Donigian Park are curiously all located in small low-crime corridors between various regions of greater crime clustering. Merino Park is the only park closely situated to a particularly high-crime region; it's southern border essentially touches a small hotspot. This observation doesn't indicate that these park areas don't have crime issues - looking at the quantitative summary of criminal violations for the various park regions shows some high rates of certain crimes. Yet relative to other areas of the city, they are not located in major hotspot areas. The map can give a good indication as to which
parks might be vulnerable to crime and safety issues due to their location
in crime hotspots. These parks might be of interest in future studies
of such issues in Providence, and could be used by the Providence Parks
Department to understand which parks might require more attention to crime
and safety concerns. Detailing these parks doesn't indicate a belief
that these parks will be ravaged by crime - there are many factors that
affect how a park will be impacted by the dynamics of its surroundings.
It merely suggests that they might be susceptible to some issues that
can be associated with high crime. These might be as small as graffiti
or vandalism, yet even such small matters might lead to bigger problems
(see Park Challenges). The most significant limitation of the crime data is that it did not include any information on crime within parks. All the crime reports in the database were associated with a residential or commercial property; none were related to park crime incidents. This means that I had no quantitative concept of crime occurring inside a park, and any information I could acquire was of a qualitative nature. Furthermore, analyzing the calls for service database (which includes all incidents where the police were called to respond, and not just those that were written up as reports) would render a more comprehensive picture of the crime situation in an area. Another major limitation is related to the fact
that GIS mapping analysis is only as good as the data. The geocoded data
(see Park Crime Methods) used as the
basis for the density maps displayed a 90% matching rate, meaning that
90% of the crime reports were associated with an address and consequently
mapped. Although this is quite a high rate, it still means that 10% of
the data was not mapped because it could not be matched to any address.
This reflects problems in the database such as incomplete addresses, addresses
that were incorrectly recorded, spelling mistakes, etc. Since it was such
a large database, these errors could not all be manually solved, and are
reflected in the incomplete picture shown by the GIS maps.
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