Addressing Stereotypes Through Data by Ethan Owen
Stereotypes exist for all kinds of people and situations. People are stereotyped by their race, income, by what they wear, where they go to school, which sports teams they root for and what kinds of cars they drive, among countless other things.
Arkansans are not immune to stereotypes. Some of those include that they are inbred, marry their cousins, are hillbillies, have little education, racist and lazy.
There also exist stereotypes of areas where unemployment is higher than other places. One might assume that places with high unemployment are home to unusually high crime rates. Those with or without jobs and what little income they can get must turn to criminal practices to get by or be more violent than their sister cities where the money is and the jobs are.
Living in Arkansas for nearly four years, I have heard some stereotypes about certain areas of Arkansas. Harrison is a Ku Klux Klan hotbed, Little Rock is the ghetto, but not as ghetto as Pine Bluff and Northwest Arkansas is only nice because of the businesses in Bentonville and Springdale and the University in Fayetteville.
Before looking at the data given to us and trying to determine the best way to explore some of these stereotypes, we need to recognize that larger cities, because of bigger populations, have larger rates of crime. More people means more crime almost everywhere in the world. Smaller towns have higher unemployment because of a lack of employers. These are generally accepted statements.
With Arkansas crime and census data for the years 2012 and 2015, I wanted to do more than just look at what changed over time. The data had plenty of opportunity for exploring trends of what increased and what decreased and exploring the reasons why.
I wanted to see if the data would confirm the possible stereotype that places with higher unemployment rates had equally high violent crime and property crime rates. I had trouble coming up with the best way to present the data, but what I ended up with made the most sense for what I could do with the data in Tableau.
The tables show a descending line of property crime and violent crime rates, while the orange bars show unemployment rates. With these tables we are able to visualize whether or not cities with high unemployment do in fact have high crime rates.
Many cities have higher crime rates than unemployment rates. The table also shows that almost none of the darkest orange bars that indicate cities with the highest unemployment rates also have the highest crime rates.
Little Rock, the most populated city in the state, had an unemployment rate of 9.1 percent in 2012 and 8.1 percent in 2015, both somewhat high, but not as high as other Arkansas cities/towns. Little Rock was also the most violent city in Arkansas in 2015 with a violent crime rate of 5.2 percent and sixth in the state in terms of property crimes with a rate of 9.1 percent. In 2012, Little Rock was the third most violent city with a violent crime rate of 5.7 percent and tenth in terms of property crimes with a rate of 9.9 percent.
These statistics would seem to confirm the stereotypes of Little Rock as a high crime area, but it is also the city with the most people.
Fayetteville in 2015 had an unemployment rate of 6.3 percent and a property crime rate of 7 percent. The higher property crime rate than unemployment rate could be explained by the high number of college students. College campuses are known for places where thefts are common.
These are only a few examples of what can be discerned from the data. The point of visualizing the data in this manner was to see if there was validity in assuming places with high unemployment rates would have higher crime rates.
Data can allow us to see whether stereotypes have any truth to them, but both can be problematic.
https://drive.google.com/a/email.uark.edu/file/d/0Bw9GsZ2TKiTRMDQyYnNaQW9NQzA/view?usp=sharing
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