WDVA: Stats needed more specificity, expert analysis.
Plaintiffs who sued a police officer for discriminatory traffic stops could not prove their selective-enforcement claim with statistics that failed to establish true comparator groups and to incorporate interracial base rates for committing the offenses at issue. Background Plaintiff Rodney Hubbard and his mother were driving north on Route 29 in a black SUV. Entering Albemarle County, they passed Defendant Andrew Holmes standing outside his patrol car. A mile or two later, Hubbard noticed that Holmes was now following them in his patrol car. Holmes followed Hubbard for three to four miles before passing him. After another mile or two, Holmes again began to follow Hubbard and ultimately pulled him over, claiming that Hubbard had driven 65 mph in a 60 mph zone. Hubbard did not have his Virginia driver's license (a check later revealed it was suspended), but Hubbard provided an identification card. Holmes said he smelled marijuana and searched Hubbard due to the odor. Holmes then placed Hubbard in handcuffs in the patrol car while Holmes searched Hubbard's vehicle. Other officers arrived to assist in the search of the vehicle, but they found no drugs. Holmes issued Hubbard a ticket for driving on a suspended license. Statistics The Defendants have produced statistical data showing the racial breakdown of Albemarle County, a more specific racial breakdown of two sectors of Albemarle County where Holmes primarily worked, Holmes's total traffic stops (although these stops are not broken down by race), the racial breakdown of the summons and arrests issued by Holmes, and the racial breakdown of citations and arrests for other officers in Holmes's primary sectors for 2015. According to this data, the population of Albemarle County is 81 percent white and percent black. Holmes normally doesn't cover all of Albemarle County, but is usually assigned to three sectors. The population of two of those sectors was approximately 68 percent white and 18 percent black. No accompanying demographic data are available for traffic stops unless a summons or citation is issued. In 2014 and 2015, 17 percent of summons issued were to black individuals. From 2009 to 2015, 49 percent of the summonses Holmes issued were to black individuals, and 51 percent were to white individuals. In 2015, 51 percent of the summonses Holmes issued were to black individuals and 48 percent were to white individuals. Other officers in two of Holmes' three sectors issued 22 percent of summonses to black individuals and 74 percent to white individuals in 2015. In 2015, 61 percent of Holmes' arrests were of black individuals and 39 percent were of white individuals. Selective enforcement The central question in this case is whether a jury could reasonably rely on these statistics to find that Holmes's actions had a discriminatory effect. To prove their selective enforcement claim, the Plaintiffs must present evidence demonstrating that the government's enforcement process had a discriminatory effect and was motivated by a discriminatory purpose. If the above statistics do not show similarly situated individuals of another race were treated differently than the Plaintiffs, they don't have sufficient evidence to make out the first element. Nevertheless, the Plaintiffs think they shouldn't be required to offer a comparison of similarly situated individuals who were treated differently. They argue that selective enforcement cases are different than selective prosecution claims because it would be impossible to prove that similarly situated white drivers were not stopped and/or searched as there are no records of who is not stopped and who is not searched. But this proposition conflicts with binding law in this circuit. In United States v. Hare, 820 F.3d 93 (4th Cir. 2016), the 4th Circuit said it was adopting the selective-prosecution standard in United States v. Armstrong, 517 U.S. 456 (1996), as the standard for proving selective enforcement. Under this standard, statistics can be used to prove selective enforcement if they provide information about similarly situated classes of people who were treated differently. This court will take Hare, and 4th Circuit case law more generally, at its word and treat selective prosecution and selective enforcement claims alike. As in the selective prosecution context, then, the Plaintiffs' statistical evidence must put forward evidence about similarly situated individuals with no distinguishable legitimate enforcement factors that might justify making different enforcement decisions with respect to them. Similarly situated individuals There are two primary reasons why plaintiffs' statistical evidence is insufficient to support a finding of discriminatory effect. First, the Plaintiffs don't have a means of telling whether the data represent similarly situated individuals. None of the statistics provide a racial breakdown of Holmes's traffic stops and searches. While there's a demographic breakdown of his summonses and arrests, the Plaintiffs haven't produced any evidence that provides a reasonable basis to infer that this data concern only traffic summonses or arrests. Instead, the data appear to include all summonses and arrests instigated by Holmes and other officers located in specific police sectors. Statistics about the racial demographics of Holmes's general summonses and arrests don't provide information about classes of people similarly situated to the Plaintiffs because the data aren't broken down by the crime charged or the reasons someone was arrested. Officers would reasonably respond differently to a 911 call about domestic violence than someone speeding. The similarly situated analysis set out above requires something more rigorous than comparing Holmes to officers who were responding to different types of crimes for different sets of reasons. More generally, the Plaintiffs haven't presented sufficient information about what exactly is included in these statistics. Do the comparison officers include all officers that have spent any time in the same areas as Holmes? Even if 99 percent of their time is elsewhere? Did these officers have similar assignments? Or were some tasked with targeting certain crimes? Do the listed summonses and arrests only include interdictions instigated by the listed officer? Or do they also include responses to dispatcher calls? The court doesn't imply that every one of these answers would need to be answered, but the Plaintiffs must provide more information than they have about what their statistics mean. Relatedly, reliance on summary statistics without expert testimony or statistical analysis is problematic. In various types of racial discrimination cases, courts have frequently found that raw statistical evidence requires guidance from the proponent's expert. Here, because so little is known about the content or input data of these statistics, expert testimony would help explain what sort of deviations are or are not explained by innocent reasons. Without more, a jury couldn't reasonably find that Holmes's stops and searches had a discriminatory effect on the Plaintiffs. Base rates The second problem with the Plaintiffs' statistics is that they don't provide information about the rates at which individuals of different races commit the crimes underlying the interdictions. In Armstrong, the Supreme Court said the presumption that all people of all races commit all kinds of crime proportionally was at war with statistics from U.S. Sentencing Commission, and courts have applied this logic to traffic offenses. Here, the Plaintiffs' statistical evidence doesn't compare the arrests and summonses to demographic data about the incidence of the underlying crimes. This second problem further demonstrates the depth of the first. Without more information about what the crimes underlying the various summonses and arrests included in the data are, a jury couldn't know whether the different officers were responding to the same sorts of incidents. Even if one assumed they were, the jury would then have to assume that individuals were committing the various crimes that led to these incidents at the same rates. But, again, this inference is foreclosed by Armstrong and the 4th Circuit cases that follow it. Accordingly, the Plaintiffs' statistics can't bear the weight the Plaintiffs put on them. Thus, their claims fail as a matter of law. Motion for summary judgment granted. Hubbard v. Holmes, Case No. 3:16cv18, Apr. 20, 2018. WDVA at Charlottesville (Moon). VLW No. 018-3-154, 14 pp.
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|Title Annotation:||US District Court for the Western District of Virginia|
|Author:||Lightle, Rebecca M.|
|Publication:||Virginia Lawyers Weekly|
|Date:||Apr 23, 2018|
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