Perceptions of Crime in Norman Oklahoma
Sarah Thomie
University of Oklahoma
Abstract
Since crime is an important part of society, it is important to study. Perception of crime is also significant because it can have some of the same effects as actual crime statistics for an area. If people believe crime is somewhere, they are less likely to want to live or work within that area. The resulting problems that will follow will create a cycle that will be hard to pull an area from, unless those perceptions are fixed. If they are fixed, then a community has the chance to pull itself out of the poverty cycle into becoming a better community.I will be taking surveys of people throughout Norman, Oklahoma to see where people believe crime to be located. Part of the surveys will be demographic questions to get a sense of the variety of people, along with a map of Norman for people to highlight where they believe crime is located. With that data, I will create maps with overlays for the different demographics to compare to the true crime map, put out by the Norman Police Department. There have been different studies about crime perceptions and how other have completed these studies, but there has not been a comparison study between the perception and the reality.
Introduction
Crime is an integral part of human society, along with its counterparts, law and order. Crime can range from so-called victimless crimes, crimes against self (Ellis, 1988), to violent crimes, where mortality can be the result of committing them. Police have to tend to this wide range in the hopes to stop future crimes, both victimful and victimless. Crime analysts work to try to find where crime takes place and where it will have the most impact for the deployment of police forces.Perception is how humans look at the world around us. We see the world for want we want to see it, avoiding or ignoring the parts that we do not like. So, our perceptions of the world become our reality of our world, and for some people, they are never able to see outside that narrow worldview. People’s perceptions can change over time, as they gain experience in the happenings of the world around them. These experiences, good and bad, are able to turn people towards or away from certain viewpoints.I want to understand where people believe there to be crime to see if there is truth behind those beliefs in comparison to the actual crime maps. This is important, because crime does not just hurt people in the sense that they are harmed by the crimes themselves, but the areas are also harmed. If an area is deemed to be crime-ridden and unsafe, people will not want to live there. This depresses property values and, in turn, creates a maelstrom of issues. People will stop caring about their neighborhoods, creating the broken window effect. People will not pay as much in taxes due to the decreases cost in the property values, which makes the infrastructure and the schools for that area to have less money to spend on the students. Then those schools become havens for criminal outside elements, as the people in those schools are desperately needing a way out. By figuring out where crimes are perceived, there is also a chance that people can see where the crime actually are to either stop or to mitigate the damage that the wrong perceptions have caused.The research main questions that I want to answer are:What seasons do respondents think that crime happens most?What times do respondents believe crime happen most?What types of crime do respondents think Norman has more often than others?Where do respondents perceive the majority of crime in Norman is?
Research Context
There is one overarching question that I plan on investigating throughout this paper. Where do people perceive crime to be in Norman, Oklahoma? By looking into where people believe crime to be, I can compare between the perception versus the reality of the crime situation in Norman, OK. This is important, because crime is not just a single part of the human equation. Crime effects other people, even in victimless crime, and how those perceptions effect different areas of the city. Do people shy away from living, working, or going to different parts of Norman because they perceive crime to be there? Do diverse demographics see crime in various areas differently? Is there an association or correlation between where people perceive crime to be and other parts of what people hold dear, such as good education, higher or lower property values, and other things that these taxes pay for that will raise an area from being crime ridden to a better community? If there are perceptions different than where crime is, why is that? Why do people feel that way about certain places and locations?To answer these questions, first, I will define the differences between perceptions and the reality and how it could affect everyday life. Second, I will look into what people have already studied, trying to find footing in what has been learned. Third, I will show why we should care about why people believe crime to be in areas where it is not. Fourth, I will then look into some of the unintended consequences, where things like property values, education, infrastructure become lesser than they need to be because of areas that have become depressed from the label of crime-ridden. Lastly, I will look into Norman, Oklahoma specifically and lead into the methods and data collection.In their study, Summers and Caballero (2017), noticed that there are two types of places for crimes, the Crime Generator and the Crime Attractor. The Generator would be places where people gather in larger groups, such as shopping districts, train stations, bus stops, etc. With the higher amount of people, the criminals are able to blend in and end up with a higher number of targets they can get through. Crime Attractors are places where the criminals go to commit crime, such as gang areas and drug markets. In their study, they specifically looked at whether having Generators and Attractors in the same area would have an additive, multiplicative, or no effect on the crime in that area. They used a Monte Carlo method, a probability model with a large randomly generated numbers to find an approximate-solutions to a numerical problem that would be difficult to solve by other methods (Google, 2019).There is a very popular saying about people “growing up on the wrong side of the [railroad] tracks.” This colloquial phrase comes from when towns in the United Stated were separated by railroad tracks, with one side having the middle to upper class residential and commercial areas. On the other side of the tracks were the factories and lower classed residents, categorized with shacks and tenements (Price, 2011). The railroad tracks became the lines drawn in the dirt due to the amount of them, as there were too many roads to separate communities, and there were too few rivers to accomplish that same task (Ananat. 2011). There was a prevalence of railroads, but nothing compared to the number of roads that lined the landscape.As these towns grew up in the early to mid 1900s, it is easy to see where that thought would grow and propagate into the local populace until it became fact that the wrong side of the tracks were prone to more poverty and crime. In many cities the railroad tracks delineate the differences between the white and African-American communities from the times of segregation, as African-Americans were unable to get loans for better housing from the banks, until the enacting of the Fair Housing Act (Ananat, 2011). Being from the “wrong side of the tracks” was an indicator that you were less-than those who were able to purchase homes on the “right side of the tracks.”People have studied crime in different areas for as long as crime has been an issue in society. There have been different ways criminologists and crime analysts have studied crimes. Some researchers looked into the different demographical factors to see who perceives crimes in different ways, such as Clemente and Kleiman (1977) and Schafer, et al (2006). Others just looked to see if there was a correlation or association between what people perceived to be incivilities and higher crime rates, like Perkins, et al (1992) and Wyant (2008). Some people have looked into specific groups, such as police within an area, including McLaughlin, et al (2007) and Ratcliffe and McCullagh (2011).Clemente and Kleiman (1977) studied how crime perceptions were measured in the mid 1970s, with specific looks into how different demographic factors influence how people perceive crimes. They looked at sex, race, age, socioeconomic status, and community size to see if there was a single variable that would predict what kinds of people would have a fear of certain crimes in certain areas. They discovered that sex and community size were larger factors than the other factors they tested, and they were able to classify 72% of the sample as to be fearful of crime or not (Clemente & Kleiman, 1977).Schafer, et al (2006) looked into the gender contrasts of who perceived crime differently. They specifically studied the contrast between perceptions of safety and fear of personal and property victimization between the two sexes. They discovered that there were significant differences in the personal and property victimization questions. Women were significantly more worried about personal victimization (attacks in, around, and outside their local areas and home). Though there were differences, overall, the study they conducted had a low to moderate level of fear within that community (Schafer, et al, 2006).There were similarities between Clemente and Kleiman (1977) and Schafer, et al (2006), but there were also key differences. They both looked into a very basic demographic separation of people into an almost 50/50 split. By studying gender as their focus, Schafer, et al (2006) were able to keep their study contained to a pinpoint focus between the genders, since non-binary was not fully in the public eye yet. In contrast, Clemente and Kleiman (1977) did not go into as much depth between the genders, instead opting for a shallow, but all-encompassing, approach. Both discovered that sex and gender were exceptionally important to see how much more women were worried about safety and crimePerkins, et al (1992) looked into how the how the physical landscape affects how people perceive crime to be within an area. They looked into the “broken windows theory,” where the physical disorder is characterized by broken windows, vacant buildings, abandoned cars, and vacant, trash-filled lots (Britannica, 2019). The social disorder was another part of what they looked into, where aggressive panhandlers, noisy neighbors, homeless people, prostitution, drug dealing, public drunkenness, and groups of young adults and teenagers gathering on street corners created environments where people do not want to associate with (Perkins, et al, 1992; Britannica, 2019). They found out that with higher levels of these two different types of disorders, people tend to believe there is more crime within that area.Wyant (2008) took a multilevel approach to perceptions of crime, also looking at incivilities and disorders that Perkins, et al did. They completed their study in 45 Philadelphia neighborhoods to see which neighborhoods would be more fearful due to the incivilities that the respondents saw or thought they saw. They noticed that when these neighborhoods experienced more crime risk, they also experienced more fear of crime. They also revealed that if nearby areas had higher crime and incivilities than the respondents’ own, they would survey as more fearful, as the respondents thought that the criminals would move throughout the area (Wyant, 2008).Perkins, et al (1992) and Wyant (2008) looked into how the physical and social landscapes were able to become important to where people perceive crime to be. Both studies looked at what people believed to be incivilities, what places or behaviors the respondents thought were bringing the neighborhood down in terms of safety, value, and order. Perkins, Meeks, and Taylor (1992) stuck with the individual disorders and how they affected the people in those locations, compared to Wyant (2008) who looked at more than one variable to see where people in these locations believed crime to be.One of the mitigation factors for cleaning up these disordered areas would be the presence of police. Police would not just be there to stop crime as it happens, but their presence would also become a deterrent to criminals within that area. Though Grabosky (1996) stated that there are unintended consequences for a rise in police pressure on an area, many police departments stick with “the more the better” style of placing officers on their beats.McLaughlin, et al (2007) studied police officer perceptions of crime with three English police basic command units. They looked into how police officers knew where burglaries happened over time. They were trying to see if police had a better spatial distribution of crimes, focusing on burglaries. They discovered that police officers within these three units had an accurate idea of where these burglaries were over time, but they noticed shortcomings for short-term hotspots. They rationalized that it was due to the dynamic nature of short-term hot spots over the static nature of the long-term ones (McLaughlin, et al, 2007).Ratcliffe and McCullagh (2001) also looked into how police officers perceive crime. They looked into the idea that police are moving into a more proactive approach to policing. They used both police officers and small-focus groups for their data, collecting answers from a survey from the two sets of groups. They compared the two maps, to see that the police have a better spatial view of where crime is. The focus-groups ended up giving more of the perception of where they believed crime to be, as they did not have the insider knowledge that the police officers had. Even with that better spatial awareness, the officers were still under the belief that “their” beat had more crime than the other ones, even if they all had similar crime statistics (Ratcliffe & McCullagh, 2001).McLaughlin, et al (2007) and Ratcliffe and McCullagh (2001) both looked into the police perceptions of where crime is located. They both saw that the police were able to have a better spatial awareness of where crime was, but as, McLaughlin, et al (2007) noticed, they were better at seeing where there were long-term patterns of crimes. By looking into how the police saw different areas, both studies were able to surmise where the police believed to have the best allocation of resources.Bowers, et al (2004) looked into crime mapping to see how one crime will beget new crimes in that area. They learned that if a burglary was to happen in one house, there was an elevated risk of other homes within a 400-meter radius. They suggest that with the right kind of crime mapping, they can take the data, such as the modus operandi of the burglar, the security of the home, and the items taken by that burglar, in order to effective send out police on their beats to deter more burglaries within that area (Bowers, et al, 2004). By using Geographical Information System technologies to track crimes within different areas, they believe that this method of predicting crime than what the police were using at the time. This is a different type of crime perception, as it was done by computers instead of people, but the results are the same. Police will be sent out to different areas, where the computer believes crime to be, based on past crimes.Then comes the question of why do we care where people think crimes are? Crime is not just linked to the people that are a part of the crime (perpetrator, victim, or witness), but it is also a part of the area that they occur in and around. Crime has an effect on other people as well as the area around and in where the crime has taken place. If crime only affected those who were within first-degree of separation of the crime, then thinking of the perceptions is not important. Those in the first-degree of separation, personally affected by crime, would have their experiences, then nothing beyond them. But crime is not just a personal experience. It is a statistic, something tracked from the local, to state, to federal level. People who live nowhere near crime zones also make their choices based upon those zones.The Federal Bureau of Investigation is given the data about crimes that are reported within every city and state in the United States, and they put together a Uniform Crime Reporting (UCR) Program data sheet with all of the basic statistics of these crimes. We can use the FBI UCR compare the 2017 crime statistics between Long Beach, CA (a city to the south-south-east of Compton) and Compton, CA. Long Beach had 31,525 crime reported for a population of 471,397 people (66.88 crimes per 1000 people). Compton had 7,549 crimes to 97,728 people (77.25 crimes per 1000 people). Despite the relatively low difference in crimes per 1000 people (less than 11), Compton is known for being a ruthless, murderous, dangerous area, while Long Beach is a touristic paradise. It is this kind of perceptions that can and do cause unintended consequences to those areas.In the 1990s, crime in the United State dropped drastically, including a 43% drop in homicide rates, 34% in violent crime, and 29% in property crimes (Pope, 2011). Pope and Pope (2011) studied how the decrease in crime had an increase in property values between 1990 and 2000. They looked into the correlation between crime statistics and the median housing prices for an area. They found that there was a correlation between the two by using a scatterplot to compare the change in crime rates to the change in housing costs. There was a 7% to 19% increase in the property values they studied. They also looked into how this drop in crime can become a positive feedback loop.This loop is also studied by Gibbons and Machin (2008), who looked into how the houses in different areas can cause the increase of the areas around them. For example, they looked into how different neighborhoods have better amenities because of the areas that they are located in with relation to nearby homes. They found that in higher cost neighborhoods, the area around them reflect that higher cost, in ways such as local churches, availability of certain local retail shops, and even things like water accessibility and quality (Gibbons & Machin, 2008). They used a multiple regression analysis to study the values we put on places, such as homes and businesses.One of the main points that was looked at for the Gibbons and Machin (2008) study is schools. People who buy higher priced homes send their children to higher quality schools, due to the local property taxes that are levied to pay for the schools. These higher quality schools create a higher quality education for their students. With better education, those children can grow up to make more money than their peers from schools with a lower property tax cost. Then these children have kids of their own in higher priced neighborhoods, continuing the cycle. In the other kinds of schools, where they are unable to get those higher property taxes, those kids are more likely to stay at or below the poverty line, because poverty begets poverty (Kraay & Mckenzie, 2014).Where do perceptions fit into this? Even if an area does not have crime, but it believed to have a high crime rate, there is the same feedback loop. People are unwilling to live there for higher costs, because they can choose to live in better areas, spending their tax dollars in those higher quality areas. This leaves the areas with higher crime perceptions to lose out on that positive feedback. Instead, those areas become depressed and impoverish, if t
Data and Methods
In order to conduct my research into the perceptions of crime in Norman, Oklahoma, I used a variety of methods in order to gather the data needed. I used a survey in order to collect the perceptions of a random sampling of the populace. There were various ways to gather the surveys for the information I needed. There was an issue with using survey data, such as self-selection bias, but I do not think it skewed the results. Then, I compiled the data into maps with different demographic categories, separating out where various respondents believe crime to be, which created a series of maps of from the different demographic categories. Finally, I compared the maps between what the respondents have written with what the Norman Police Department has for their crime map.First, I created a survey with demographic information, such as race, income, gender, and age (Appendix A), along with three extra questions for the respondents to answer. These questions were about crime seasonality, crime times, and types of crime, followed by a map of Norman, Oklahoma where the respondents marked where they perceived and believed crime to be the most active on an image map. The map had roads and railroad tracks marked for reference on it. Curtis (2012) noticed that using a preprinted base map would make it easier for respondents to answer the questions I am asking. He also brought up a paper by Pocock, where Pocock (1976) “notes that the instructions provided to participants, size of paper, and the shape of the paper can all influence the results” of the map part of the survey.Doran (2005) used the sketch maps to get people to show them where they respondent was afraid of going to and into, due to their fear of crime within that area. They combined the collective responses from both the sketch maps, as well as with the question asking the severity of their fear of an area. The maps were then digitized, weighted against the degree of avoidance of those areas. They also did timed maps for specific times of the day to see which areas people would avoid at different times of the day. This is why I chose to ask people to choose when they believe crime happens most.Online surveys have become more and more popular as the internet has become a standard access point for people in America. Getting the surveys out to people is the hardest part of the online survey collection, as well as the worry of not getting to every demographic (Campbell, 2018) that would represent Norman, OK. There is not an email address White Pages, so the data collected would be based solely on people who use Social Media, such as Facebook, Reddit, etc. I would also be able to upload the map image to the survey site, allowing the respondent to fill in where they believe crime happens. Within this method, I was limited with what the survey collection software allowed for answers on the maps. It allowed me to do single points for respondent answers.I chose to do an online survey format due to not being within the target survey area while collecting the survey responses. Specifically, I sent out the surveys through various Facebook groups that were linked to Norman, OK, such as the various Ward pages and a larger community page. There was some overlap in members, but when comparing the respondent demographic data, I do not believe there was anyone who chose to do the survey more than once. By using Facebook, I was able to collect 341 responses, which yielded _ total points between the five different maps.For the maps themselves, I ended up using an image of the City of Norman that extended from 60th Ave NW (for the Western boundary) to 36th Ave NE (for the Eastern boundary), then the North and South city limits to complete the map bounds. I allowed the respondents to use up to ten points to mark where they believed different crimes are located. This allowed me to separate out where they perceived different crimes take place. This made it easier to create different maps and to see where there is an overlap. I had five image maps per survey for each of the different types of crimes, such as violent, nonviolent, property, drugs/alcohol, then an overarching map of where the respondents thought where overall crime was located.After the surveys were completed, I created the maps themselves. I created a hotspot map with spatial standard deviations of the data (Caplan, 2011). I used the combination of demographics and the hotspot maps to create a series of 275 maps that were separated by the respondents’ different demographic combinations. By combining both of these data points, I was able to create a series of maps to compare to the actual crime map.Some issues I expect to find are going to be in the way the respondents answer the surveys. On the online survey, they are locked into answering only one of the answers at a time, as well as forced to answer all of the questions. Then, with the online image maps, I was limited in what the software will allow me to collect from people. The largest issue was being forced to use an image of the map instead of a map where the person could zoom in and see specific areas or names of non-major streets.Another problem I expected to have is a self-selection bias in the online surveys. This was due to the fact that people are more likely to respond when they have strong feelings for or against something (Whitehead, 1991). Even though Whitehead (1991) studied the effects of self-selection bias in mail in surveys, it can also be applied to ones that were sent out through social media sites.
Results
At the end of the three-month survey period, there was a total of 341 responses from throughout Norman, OK, ending up with 17,000 total points between all of the maps, with 3400 for the map that contains where the respondents believed all crime in Norman occurs most, along with 3400, 3400, 3400, and 3400 points for where respondents believed the violent, non-violent, property, and drugs and alcohol crimes (respectively) occurred most often in the City of Norman. In all of the maps, the darker the shade of red, the more often the respondents chose that specific area with a point during the data collection.Appendix B has the actual crime maps from the Norman Police Department and the Cleveland County Sheriff’s Offices for the various types of crimes that were used for the different categories of crimes for their respective maps. Appendix C has the respondent demographic bar charts. There are also the maps that were created by Qualtrics, as well as the all of the raw data points that made up the respondent answers. Appendix D is the composite charts with all of the respondent answers for each of the different categories of crimes. Appendices E-I are all of the different demographic maps for each of the different crime categories (i.e. All Crime, Violent, Non-Violent, Property, and Drugs and Alcohol).
Conclusion
Crime is something that we all have to deal with every day, even if it is something not at the forefront of our thoughts. We care about the perceptions versus the reality in crime to see where people are more likely to avoid, due to their thoughts of where crime is. It could be something as seemingly simple as not driving down certain streets, to circumventing entire areas of a city. The perception of high crime in an area can drive down an area’s value, even if there is nothing else wrong with that area of the city. That will cause an effect on the basic standard of living within those areas, which can cause a cascading effect in the way of people, businesses, and city beautification efforts being driven out of a community, in search of somewhere better.I collected surveys and maps of where people in Norman, OK perceive crime to be, before comparing that data with the actual crime data. I expected to find that the maps will be different, but nothing significantly so. The actual crime maps had more specific areas where different crimes happen, and they were more precise in their images. The perceptions maps were further spread out, with the different demographics having various interpretations of where crime is located in Norman.This contributed to my major due to the topic and methods. Criminology is a complex field of study that requires knowing when and where crime is most likely to happen. By studying where people perceive crime to be, we can also utilize that information to see if there is a growing trend in an area that might not be caught by police or crime analysts. The spatial analysis portion is important, because it allows us to see visually the differences in perceptions versus reality.
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