2010-2020 Dearborn Police Citations Data
2010 - 2020 Citations Data Analysis
On February 20, 2021 we hosted a Citations Data Townhall in collaboration with the Detroit Justice Center to illuminate and address issues relating to citations and provide mutual aid alternatives to the punishment model.
For more information about the role of citations in criminalizing poverty and race, check out the Detroit Justice Center's white paper Highway Robbery.
Addressing the 2020 Effect
Citations issued by Dearborn police department dropped significantly in 2020 compared to previous years. The largest drop was in plate violations issued by the department. This was a direct result of Governor Whittmer's executive orders 47 and 78 which instructed local municipalities to stop enforcing certain plate violations.
Finding 1: Black People are Over Ticketed by Dearborn Police, and It's Been Getting Worse
In 2010, census data revealed that 3.3% of Dearborn is Black. Despite this small number of Black residents, Dearborn PD's citations have been overwhelmingly of Black people. And this disparity is growing. In 2010, Black people accounted for 27% of all citations. In 2019, Black people accounted for 47.7% of all Dearborn Police citations.
In order for these data to be representative of the number of individuals present in Dearborn at a given time, approximately 75,000 Black people would need to enter the city each day, with no additional white-classified people entering the city.
Proportion of DPD's citations that are of Black people by year.
Dearborn Population by Race, 2010 Census Data
(Arab Americans are classified as white in these data)
2019 Dearborn Police Citation-Violation by Race
(Arab Americans are classified as white in these data)
Finding 2: In 2019, More Black People were Cited than White-Classified People
In 2019, 14,503 citations - violations were issued to Black individuals, while 12,435 citations-violations were issued to individuals classified as white. In a city where less than 4% of the population is Black, and nearly 90% of the population is classified as white this is a huge disparity.
Finding 3: Dearborn Police are Punishing Poverty
For each year of data, the top four categories of citations issued are fines written for violations that result from individuals not being able to afford to upkeep or document their vehicles:
No proof or no insurance - $175
Driving while license suspended/revoked/denied
Defective equipment - $120
No proof of or no registration - $120
The majority of citations written by Dearborn police are for plate violations (52%). Plate violations are issued for reasons unrelated to driving behaviors and instead reflect an individual's ability to document their vehicle.
Plate violations are being issued to drivers with no corresponding moving violations. In the years 2009-2019 Dearborn police issued 53,149 "no proof of or no insurance" violations and 41,508 moving violations. In at least 11,641 circumstances Dearborn police issued plate violations with no citable moving infractions.
Finding 4: When Dearborn Police Punish Poverty They Punish Black People
2009 - 2019, citation types with the highest proportion of Black recipients are overwhelmingly categories that indicate the presence of poverty and/or economic need. Plate violations were issued to Black men at a rate 110 times that of white-classified women, and 73% of all Driving While License Suspended citations are written to Black people.
These numbers can be compared to the citation rates for moving violations which demonstrate significantly lower rates of racial bias.
Finding 5: White Women are Underrepresented
According to the 2010 Census, women classified as white make up approximately 45% of Dearborn's total population. In the data provided, white women make up no more than 12.7% of citation-violations in any given year. The citations issued to the highest proportion of white women were citations that could be objectively identified and could have resulted in harm to another individual:
Failed to yield - damage accident
Speed 1-5 over
Disregard stop sign
Failed to stop within assured clear distance - damage accident
Speed 6-10 over
Finding 6: Individual Officers' Racial Bias Goes Unaddressed, and Gets Worse Over Time
Of the 14 officers who issued 60% or more of their citations to Black folks in 2018, 11 returned in 2019. For almost all of these officers who returned in 2019 racial bias remained high. Eight of these officers' racial bias increased between 2018-2019.
Across the whole dataset, a comparison of changes to individual officers' level of bias in citations issued 2014-2019 demonstrated:
The largest proportion of officers showed no significant change in bias
More officers showed an increase in bias than showed a decrease in bias
Increases in bias were larger than decreases in bias
Any individual-level interventions that are currently in place at Dearborn Police Department are insufficient to identify and/or address individual officer biases. We recommend implementation of accountability measure to reduce opportunities for officers' individually held biases to influence their work.
Individual Officer Bias 2018-2019
Finding 7: Citations with external accountability measures show lowest levels of bias.
Across all citation categories, Black people are overrepresented, and white-classified individuals are underrepresented. In 2019, the citations categories with the highest proportion issued to white-classified individuals were for speeding. Speed-checking radar guns provide an objective measurement that can partially -- but not fully -- compensate for officers' individual biases, and biases created by the design of patrol routes.
White women are underrepresented across all data categories. The citation category in which the sex and race distribution was most similar to Dearborn's population was "failed to yield - damage accident":
Black women: 5%
Black men: 6%
White-classified women: 34%
White-classified men: 41%
Other/unidentified race/gender: 14%
"Failed to yield - damage accident" citations are issued at a rate most similar to Dearborn's population because:
They are issued based on calls to service, not officer observation or patrols.
Infractions can be verified based on objective external indicators.
Multiple parties require and receive a full reporting of events.
These characteristics can serve as a model for accountability measures to reduce bias across all citation types.
2010 - 2020 Citations Data
In 2011, reports were published indicating an overwhelming racial disparity in arrests performed by Dearborn Police. In June 2020, our activists filed FOIA requests to receive all citation data from the Dearborn Police 2010-2019. This request took four months to fill, and the data have finally been received! As we are just beginning our review of these data, we would like to invite our community to review these data and draw conclusions accordingly.
Concerns regarding data quality
As we process through these data, we will record the indicators we notice which may compromise the data quality, as well as steps we have taken in our analysis to mitigate these concerns.
Absence of Ethnicity Categorization
The data do not have a categorization for ethnicity, which indicates the presence of ethnic erasure in these data. Dearborn has a significant Arab American population, as well as a Hispanic/Lantinx population. Failing to report on ethnicity does not permit us to analyze the data to identify trends in profiling based on ethnicity.
Prevalence of Unknown Race, 2010 - 2014
Between 2010 - 2014 approximately 30% of the records indicate "unknown race". Between 2015-2017 this number declines sharply, with around 11% of records indicating "unknown race" in 2019. We believe this may reflect a standardization of the policy to classify Arab Americans as white, in accordance with census data.
Duplication of Parking Citations
In the data provided, parking citations, where the recipients gender is unknown, are listed twice. The citations are listed once as being issued to an individual who is white, and a second time as being issued to an individual who is of unknown race. This trend is consistent across all datasets. In order to preserve the validity of our analysis, we have chosen to exclude all parking citation data.