Analyzing the Chicago Police Department

INST 466 Fa 20 Week 6 Research Brief Example Essays

Example 1

Analyzing the Chicago Police Department Database revealed a pattern of unsatisfactory data collection for inputting individuals into the database as gang members. An example of this is can be seen in the numerous occasions where individuals are labeled as gang members, but no affiliated gang. The most noticeable pattern discovered during the analysis involves comparing the number of individuals placed into the database by year. Surveillance technologies must be created and used in ways that do not passively ascribe race to criminality, nor should these technologies be used to spotlight anyone in a similar fashion to 18th Century Lantern laws.

The integrity of the entire Chicago PD gang member database is drawn into question when analyzing, filtering, and browsing the large list of names included. Logically, it does not make sense to label someone as a gang member without listing the related gang’s name. However, this is not the case in the Chicago database, where 2,089 individuals (47.58% Black) are listed as gang members with no further explanation provided. Aaron Harvey, a black man incorrectly listed as a gang member in California, explains how devastating it is to be wrongly accused of gang affiliations due to an outdated, prejudiced,  and ineffective system. “Despite having no knowledge of the crimes I was charged for, I was facing a sentence of 56-years-to-life because my name was in the database” (Harvey).

While comparing numbers of gang members added to Chicago’s database between each year from 2013 to 2017, a downwards trend in total number of individuals being added to the list revealed itself. Contrasting the total number of initiated gang members within the database by year revealed a downwards trend in the database’s growth. Looking at the 5 most recent years, the number of gang members added to the database is reduced by almost half each year. Chicago PD added 2320 (60.47% Black) in 2013, 1531 (56.17% Black) in 2014, 912 (49.89% Black) in 2015, 431 (47.8% Black) in 2016, and 209 (51.2% Black) in 2017. While the total number of gang members added each year is reduced, the percentage of race that is continuously included to the database still leans highly towards Chicago’s Black demographic. This is especially troublesome as the US Census estimates the Black demographic to compose only 30% of Chicago’s citizens (census.gov/quickfacts/chicagocityillinois).

Example 2

The age and racial entries in the Chicago Police Department Data on Gang Members  Database (CPDDGM) reveals negligence to keep information current and racial bias by Chicago Police that nourishes a cycle of minority crime recidivism.

Analysis of the 128,000 entries in the CPDDGM revealed 182 gang-related arrests recorded had criminals of 70 years or older, 80% of which were before the year 2000. Unless these cases are under active investigation, preliminary review in progress, or are still active within the jurisdiction, which implies these 90-year-old criminals are active today, these entries do not meet the five year retention period. In Larry Smith’s interview of the Baltimore Police Department’s (BPD) gang-liaison, he revealed making “very tenuous” associations between social groups of validated targets. Also, he mentions that after entering around 50 entries in the BPD gang database, he never felt compelled nor was expected to update the database, even after several years had passed. Because the CPDDGM only uses age, ethnicity, gang-affiliation, faction, and arrest date as unique identifiers, there is no evidence of any follow up with any of these entries. Browne described the Book of Negros to be a text link of identity to bodily markers of slaves; however, it appears our first responders have adopted a similar text-based method, except this minority incorporates all minority races.

Further analysis of the gang database reveals that out of 128,000 entries, 4% are white, 69% are black, and 25% are of Latino descent. Of those entries, 2089 are without any gang affiliation. Because they do not meet the gang related criteria, it raises concerns as to why they remain in the database today. Among those 2089, 16% are white, and 80% include Blacks and Latinos. Despite the racial disparities being less severe in comparison to the whole database, it is still an overwhelming gap of minority races incorporated without reason. Inclusion in this database categorizes someone as a potentially dangerous individual, which can make it more likely to struggle to find a reliable income source, come into contact with police more, and wind up within the judicial system.

Example 3

Cook County is a county region located in the upper northeastern Illinois. It is home to over 5 million residents, the majority of which are 65% White, 23% Black or African American, and 25.6% Hispanic or Latino. Examining the Cook County Regional Gang Intelligence Database highlights a systemically racist technology that disproportionally targets African American males, based on factors like race and gang affiliation, leading to an increase in surveillance and illumination of the black body.

When analyzing the racial makeup and sex of the gang members in the Cook County gang member database, African American males appear to be the most predominant target. Although only 23% of Cook County’s population is African Americans, approximately 43% of the prisoners in Cook County’s gang member database are Black males. Like the Book of Negroes that utilized a ledger as a tool to track and store demeaning descriptions of enslaved Africans, increasing their visibility and rendering them as less human, the Cook County’s gang member’s database technology is subjecting these black males to higher visibility. This visibility is conveyed using potentially biased database fields with information on physical features, shared dress styles, shared use of hand signs, and officers’ suspicion. By establishing features to look for, the database made it possible for the black body to be constantly illuminated… made knowable, locatable, and contained (Browne, 554) like the fugitive ads for runaway slaves that highlighted the features of the slaves. Similar to how runaway slaves were severely punished after being captured, when a person becomes classified as a gang member, people are less likely to be sympathetic to them when they are arrested and often face inhumane treatment in prison. As a result, people inaccurately classified, are subject to unjust surveillance and treatment.

When analyzing gang affiliation, gangs with predominantly African Americans appear in the database. As seen in the graph the Gangster Disciples, Vice Lords, and Black P Stones, with mostly black members, have the highest number of members arrested. This graph reflects an increased criminalization and incarceration rate for members in gangs associated with African Americans, compared to those in predominantly white gangs who tend to receive fewer media and public attention. This practice of targeting primarily African American gangs is similar to when police commissioner Anthony Batts in Baltimore, directed attention towards The Black Guerilla Family. He claimed that “The Black Guerilla Family was a major contributor to a rise in drug-related violence” (Smith, 2018) when Baltimore murders reached 217 in 2012. As a result of this accusation, database technology was used to inaccurately validate primarily African American males, as gang members. Validating and arresting these African American males, did not help reduce the crime as expected, further highlighting how the prejudiced technology served only to draw attention away from the drug-violence problem and illuminate the black body in a negative light.

Example 4

After parsingand analyzing the Chicago Police Department data on gang members, I was able to see a racial disparity between the breakdown of race classification in the data versus the racial makeup of Chicago based on data from 2010. The data classify the vast majority (~70%, my Excel formulas broke before I got exact numbers, sorry!) as “Black” or “Black Hispanic” and approximately 30% of people as mostly “White” or “White Hispanic” with a small minority of this remainder  being  of  some  other  race  classification,  while2010  data of  Chicago  demographics reflects a makeup of 45.3% white, 32% black, and 5% Asian.

I  believe  this  pattern  of  racial  disparities  in  arrest  records  shines  a  light  on what  may potentially   bethe  department’s  intentional  targeting  of  historically  socioeconomically disadvantaged groups within the city. The records that Chicago’s police have kept on suspected gang members seem to serve as some sort of ‘book,’ linking the corporeal identifier of perceived race along with other factors to a person’s affiliations. Eerily reminiscent of The Book of Negroes that Simone Browne discusses, the police department’s data entry is contemporary surveillance that allows “boundary maintenance occurring at the site of the racial body” as this data also keeps track of gang and faction affiliations, effectively reducing these people to the “unvisibility” of their skin color as it relates topotential social (gang) connections.

Examination of this data in combination with the context provided by our readings on the Baltimore  and  California  gang  databases  raises  an  alarming  question for  me about  why  there  is little accountability when it comes to discretion about the validity of data entered and kept in these systems, given the possibility for the potentially life-threatening implications for the subjects in the  databases. Questioning  why  particular  races  are  consistently  recorded  in  higher  or  lower proportions over time may lead to the exposure of a broader pattern of unchecked abuse of these legal systems as means of discrimination. Another interesting example of a modern database that has been criticized is the U.S. government Terrorist Screening Database No Fly List. It has come to the American public’s attention numerous times; one curious occasion was when senator Ted Kennedy had trouble boarding planes several times because he was misidentified as someone on a ‘selectee list.’ Given occasions such as this one  as  well  asthe  cases we  read  about  with  gang databases, the origins of such classification in The Book of Negroes (itself rooted in the violence of slavery) make it necessary to carefully explore and counteract the harmful effects of tracking that may disproportionately affect certain racial groups.

Example 5

After analyzing the Cook County Regional gang database and the Chicago Police Department data on gang members shows a pattern of black people being overrepresented in the police database.

These databases provide lots of information. They provide a list of tens of thousands of members entered into the gang database. After analyzing the data there’s a huge difference in the representation of race. In the police’s database 70% of the memebers in their database were black, and 25% white hispanic. In the Cook County database it was 43% black and 25% white hispanic. The representation of white hispanics from the two were very similar whereas there is about a 40% difference in how many black people were entered into the system. In an article in The Appeal it talks about how police commissioner Anthony Batts had to look and enter people into the gang database. He said, “I looked at supposed gang identifiers like tattoos, certain colors of clothing or accessories, hand signals, street associates, or if someone had ever been arrested with other validated gang members.” (Smith) Some of these attributes are very stereotypical and led to more and more people being added to the police’s database.

From this week’s reading we learn a lot about how gangs and how they are entered into the database. It was said that potential gang members are collected through social networking and racial profiling. This leads to people being classified as a gang member when they have no affiliation. For instance, Aaron Harvey talks about how he found out he was entered into the gang database without his knowledge just because of the area he lives in. He was racially profiled because of his skin color and the fact that he lived in a bad area. Many people, and without their knowledge, are being entered into these databases just because they are black. Some people are being entered into the database just because of who they have been seen or pictured with. Smith mentions that “When I came across one of our already validated targets in a photo with a group of people, I was often instructed to enter them into the database as associates.” (Smith) Just due to the fact that people are asocitated with a potential gang member they will be entered.

Though these actions are done to catch gang members and to protect others it indicts innocent people. Black people are more commonly racially profiled and stereotypes based on their lifestyles. This can lead to wrongfully accusing someone of a crime orlead them to a harsher punishment for just being in this database when they shouldn’t be.