Johnson et al v. Holmes, No. 3:2016cv00016 - Document 219 (W.D. Va. 2022)

Court Description: MEMORANDUM OPINION and ORDER denying 198 Motion to Exclude. Signed by Senior Judge Norman K. Moon on 08/23/2022. (dg)

Download PDF
Johnson et al v. Holmes Case 3:16-cv-00016-NKM-JCH Document 219 Filed 08/23/22 Page 1 of 14 Pageid#: 1369 Doc. 219 UNITED STATES DISTRICT COURT WESTERN DISTRICT OF VIRGINIA CHARLOTTESVILLE DIVISION BIANCA JOHNSON, et al., Plaintiffs, LEAD CASE NO. 3:16-cv-00016 v. ANDREW HOLMES, Defendant. LEON POLK, et al., Plaintiffs, v. CASE NO. 3:16-cv-00017 ANDREW HOLMES, Defendant. RODNEY HUBBARD, et al., Plaintiffs, v. CASE NO. 3:16-cv-00018 ANDREW HOLMES, Defendant. CORY GRADY, Plaintiff, v. CASE NO. 3:17-cv-00062 ANDREW HOLMES, Defendant. SERGIO HARRIS, Plaintiff, v. CASE NO. 3:17-cv-00079 ANDREW HOLMES, et al., Defendants. 1 Dockets.Justia.com Case 3:16-cv-00016-NKM-JCH Document 219 Filed 08/23/22 Page 2 of 14 Pageid#: 1370 Memorandum Opinion & Order Denying Defendants’ Motion to Exclude Plaintiffs have brought these consolidated cases alleging claims of selective enforcement of the laws and racial profiling primarily by Defendant Officer Holmes, in violation of the Equal Protection Clause of the Fourteenth Amendment. In anticipation of trial, Defendants have filed a motion in limine seeking to exclude Plaintiffs’ expert testimony from a statistician, who would testify that the likelihood of Holmes’ higher rate of citations of Black drivers versus lower rates by other officers, by chance, is about 1 in 100,000. This Court is not writing on a blank slate. This Court previously excluded the underlying statistics Plaintiffs offered as insufficient to support the element of Plaintiffs’ claim that they show Holmes’ conduct had a “discriminatory effect.” However, the Fourth Circuit reversed, concluding that Defendants had provided no reason to justify excluding Plaintiffs’ statistical evidence as a matter of law. Here, Defendants’ arguments in support of excluding Plaintiffs’ expert’s testimony largely rehash arguments made to (and rejected by) the Fourth Circuit. To be sure, as the Fourth Circuit explained, Defendants will be able to offer evidence of any legitimate distinguishing enforcement factors to a jury, as could explain the difference in the number of citations Holmes issued versus other officers. This Court will allow Plaintiffs’ expert testimony, subject of course to the regular means of challenging expert testimony, including crossexamination and presentation of contrary evidence. Issues In this motion, Defendants Andrew Holmes and Casey Minkus move to exclude the testimony of Plaintiffs’ expert, Virginia Rovnyak, Ph.D. Dkts. 198, 199. Dr. Rovnyak is expected to opine whether “Officer Holmes cited Black drivers at a higher rate than could reasonably have happened by chance, compared to the rates of the other officers who worked in 2 Case 3:16-cv-00016-NKM-JCH Document 219 Filed 08/23/22 Page 3 of 14 Pageid#: 1371 the same sectors as Officer Holmes.” Dkt. 199-2 at 1. She concludes that “the likelihood of such a high rate … occurring just by chance is less than 1.1 in 100,000—slightly over one in a hundred thousand.” Id. at 5. Thus, she “conclude[s] with a high degree of mathematical certainty that Officer Holmes’ rate of citing Black drivers is not the same as the 2015 rate for the 7 other officers who had at least 19 total citations. It is statistically higher.” Id. Defendants argue that Dr. Rovnyak’s opinions are irrelevant and should be excluded under Daubert. Defendants argue that her opinions are irrelevant because, at most, they speak to correlation, not causation. For instance, Dr. Rovnyak testified that “you can’t prove things with statistics,” but only that it is “very, very strong evidence that for some reason—and the only one I can think of is bias—[ ] that he cites Black drivers more than non-Black drivers.” Dkt. 199 at 6. In other words, Defendants argue that Dr. Rovnyak has “concede[d] that she cannot testify as to causation.” Id. Moreover, Defendants contend that she only “created that correlation by default,” because she “did not include any variables other than race. She did not account for any other factors in the traffic stops conducted by the officers.” Id. at 7. Defendants also argue that she “has no relevant experience in law enforcement” and “is not qualified to know whether or opine that she accounted for all the variables.” Id. Thus, Defendants argue, because Dr. Rovnyak had “considered no factors or information other than race … her calculations are irrelevant and will not assist the jury in any manner.” Id. Separately, Defendants argue that she had “insufficient data to render a reliable opinion.” Id. For one, they contend that Dr. Rovnyak “only included seven other officers,” and the data provided “did not specify the type of offense,” nor “specify nor identify whether it is the same individual or interaction resulting in the citation,” or “the number of shifts spent in Sectors 1 and 2.” Id. at 7–8. Defendants also criticize Dr. Rovnyak because she did not “run any tests for 3 Case 3:16-cv-00016-NKM-JCH Document 219 Filed 08/23/22 Page 4 of 14 Pageid#: 1372 clustering and independence” in her statistical analyses. Id. at 8–9. And Defendants contend that, “[b]ecause [her] data is insufficient, she is not comparing ‘apples’ to ‘apples’ in her statistical analysis.” Id. at 9. They fault her for “assum[ing] that each citation corresponds to a traffic stop,” but “there is no factual basis for that assumption,” and “[t]here can easily be multiple citations in one traffic stop.” Id. at 10. Thus, Defendants conclude, that “[w]ithout knowing whether these citations correspond 1-to-1 with each individual and without knowing the nature of the offense, Dr. Rovnyak is not comparing apples to apples in her analysis.” Id. at 11. Concluding that her opinion “is irrelevant, uses unreliable methodology, lacks sufficient foundation and [would] not assist the jury,” Defendants argue that it should be excluded. Id. Applicable Law Rule 702 of the Federal Rules of Evidence governs the admissibility of expert testimony. Rule 702 provides that A witness who is qualified as an expert by knowledge, skill, experience, training, or education may testify in the form of an opinion or otherwise if: (a) the expert’s scientific, technical, or other specialized knowledge will help the trier of fact to understand the evidence or to determine a fact in issue; (b) the testimony is based on sufficient facts or data; (c) the testimony is the product of reliable principles and methods; and (d) the expert has reliably applied the principles and methods to the facts of the case. Fed. R. Evid. 702. Under Rule 702 and pursuant to the Supreme Court’s decision in Daubert v. Merrell Dow Pharmaceuticals, Inc., 509 U.S. 789 (1993), the district courts have a “gatekeeping role” so that they may exclude unreliable expert testimony from the jury’s consideration. 1 These principles 1 See also Fed. R. Evid. 702 advisory committee’s note (2000 amends.) (explaining that the Rule 702 amendment “affirms the trial court’s role as gatekeeper and provides some general 4 Case 3:16-cv-00016-NKM-JCH Document 219 Filed 08/23/22 Page 5 of 14 Pageid#: 1373 apply to all proposed expert witnesses with specialized knowledge, not just those based on scientific knowledge. Kumho Tire Co., Ltd. v. Carmichael, 526 U.S. 137, 141 (1999). Expert testimony is admissible under Rule 702 “if it involves specialized knowledge that will assist the trier of fact in understanding the evidence or determining a fact in issue, and is both reliable and relevant.” United States v. Young, 916 F.3d 368, 379 (4th Cir. 2019) (citing Daubert, 509 U.S. at 889–92). There is no requirement that the party seeking to introduce expert testimony “‘prove’ anything to the court before the testimony in question can be admitted,” although, “[a]s in all questions of admissibility, the proffering party must come forward with evidence from which the court can determine that the proffered testimony is properly admissible.” Maryland Cas. Co. v. Therm-O-Disc, Inc., 137 F.3d 780, 783 (4th Cir. 1998). 2 When considering a challenge to the reliability of expert testimony, courts must consider the following Daubert factors: (1) whether a theory or technique can be or has been tested; (2) whether it has been subjected to peer review and publication; (3) whether a technique has a high known or potential rate of error and whether there are standards controlling its operation; and (4) whether the theory or technique enjoys general acceptance within a relevant scientific community. Hickerson v. Yamaha Motor Corp., 882 F.3d 476, 480–81 (4th Cir. 2018) (quoting Cooper v. Smith & Nephew, Inc., 259 F.3d 194, 199 (4th Cir. 2001) (citing Daubert, 509 U.S. at 592–94)). standards that the trial court must use to assess the reliability and helpfulness of proffered expert testimony”). 2 See also Fed. R. Evid. 702 advisory committee’s note (2000 amends.) (explaining that “the admissibility of all expert testimony is governed by the principles of Rule 104(a),” and that, “[u]nder that Rule, the proponent has the burden of establishing that the pertinent admissibility requirements are met by a preponderance of the evidence”). 5 Case 3:16-cv-00016-NKM-JCH Document 219 Filed 08/23/22 Page 6 of 14 Pageid#: 1374 District courts must be mindful of “two guiding, sometimes competing, principles” when considering whether to allow expert testimony. Westberry v. Gislaved Gummi AB, 178 F.3d 257, 261 (4th Cir. 1999). First, “Rule 702 was intended to liberalize the introduction of relevant expert evidence.” Id. However, courts also must be cognizant that “[b]ecause expert witnesses have the potential to be both powerful and quite misleading,” testimony that “has a greater potential to mislead than to enlighten should be excluded.” Id. A district court’s gatekeeping role “is not intended to serve as a replacement for the adversary system,” and therefore “the rejection of expert testimony is the exception rather than the rule.” United States v. Smith, 919 F.3d 825, 835 (4th Cir. 2019) (quoting In re Lipitor (Atorvastatin Calcium) Mktg., Sales Practices & Prod. Liab. Litig. (No. II), 892 F.3d 624, 631 (4th Cir. 2018)) (cleaned up); see also Fed. R. Evid. 702 advisory committee’s note (2000 amends.) (“A review of the caselaw after Daubert shows that the rejection of expert testimony is the exception rather than the rule.”). Several other rules of evidence are also applicable to the pending motion. Rule 401 states that “[e]vidence is relevant if: (a) it has any tendency to make a fact more or less probable than it would be without the evidence; and (b) the fact is of consequence in determining the action.” Fed. R. Evid. 401. The “threshold for determining whether evidence is relevant is comparatively low …” United States v. Kiza, 855 F.3d 596, 604 (4th Cir. 2017). And Rule 403 provides that: “[t]he court may exclude relevant evidence if its probative value is substantially outweighed by a danger of one or more of the following: unfair prejudice, confusing the issues, misleading the jury, undue delay, wasting time, or needlessly presenting cumulative evidence.” Fed. R. Evid. 403. In this context, “unfair prejudice” means “an undue tendency to suggest a decision on an improper basis,” such as “an emotional one.” Fed. R. Evid. 403, advisory committee’s note 6 Case 3:16-cv-00016-NKM-JCH Document 219 Filed 08/23/22 Page 7 of 14 Pageid#: 1375 (1972 proposed rules). The “mere fact that the evidence will damage the defendant’s case is not enough—the evidence must be unfairly prejudicial, and the unfair prejudice must substantially outweigh the probative value of the evidence.” United States v. Hammoud, 381 F.3d 316, 341 (4th Cir. 2004) (en banc) (internal quotation marks omitted; emphasis in original), vacated on other grounds, 543 U.S. 1097 (2005), relevant part of prior opinion reinstated, 405 F.3d 1034 (4th Cir. 2005); accord United States v. Grimmond, 137 F.3d 823, 833 (4th Cir. 1998) (explaining that “[e]vidence that is highly probative invariably will be prejudicial to the defense,” but that Rule 403 only excludes “unfair” prejudice). Reasoning The Court first turns to Defendants’ arguments that Dr. Rovnyak’s testimony should be excluded as “irrelevant.” The Court considers Defendants’ arguments unpersuasive. See Dkt. 199 at 5. Particularly in view of the Fourth Circuit’s earlier opinion in this case, this Court concludes that Plaintiffs’ expert’s testimony would certainly be relevant to proving Plaintiffs’ claims. To start, the standard for relevance is relatively low. Kiza, 855 F.3d at 604. Dr. Rovnyak providing testimony describing the statistics of Holmes’ number of citations to Black drivers and calculations that the number was higher to a statistically significant degree than others in his department is evidence that tends to make it at least somewhat more likely that Holmes acted with discriminatory intent and with a discriminatory effect. In effect, Defendants’ argument challenges the relevance of the statistics themselves as much as Dr. Rovnyak’s conclusions about the statistics. In the Fourth Circuit’s prior decision in this case, the court explained that “[t]he law has repeatedly recognized that statistics can be used to prove discriminatory effect.” Johnson, 782 F. App’x at 277. To be sure, concerning the precise statistics at issue, the Fourth Circuit did not conclude that Plaintiffs’ statistics were “sufficient 7 Case 3:16-cv-00016-NKM-JCH Document 219 Filed 08/23/22 Page 8 of 14 Pageid#: 1376 evidence of discriminatory effect when applying the correct standard.” Id. at 281 (emphasis added). However, the court did conclude (1) that the statistics “avoid[ed] the pitfalls of the statistics at issue in” prior cases; (2) that they were “unique” and could help Plaintiffs “compare data about Holmes’s traffic stops and summonses by race with similar data from the rest of the police force and from individuals officers assigned to the same sectors as Holmes”; and (3) they “serv[ed] as a proxy to show the general racial composition of drivers on the road that Holmes could have pulled over but did not.” Id. at 282. Accordingly, while the record on appeal was insufficient for the Fourth Circuit to conclude “whether the proffered statistics establish [Plaintiffs’] claims as a matter of law,” id. at 284 (emphasis added), the Fourth Circuit’s opinion demonstrates that they certainly are relevant to support Plaintiffs’ claims. Defendants raise a variation on this argument, that Plaintiffs’ expert testimony should be excluded as “irrelevant” because it only concerns correlation, not causation. This argument fares no better. Although “selective enforcement and selective prosecution claims may be difficult to prove,” the Fourth Circuit explained that such claims “are not (and should not be) impossible to prove,” and the Fourth Circuit has further cautioned against “imposing a standard of proof that defies statistics.” Id. at 280–81 (second emphasis added). 3 To be sure, Defendants’ point is not wholly without force. “Correlation and causation are two different things.” Arredondo v. Locklear, 462 F.3d 1292, 1301 (10th Cir. 2006). But that does not mean evidence of a correlation is per se irrelevant. See Etherton v. Owners Ins. Co., 829 F.3d 1209, 1220 (10th Cir. 2016) (“Although correlation alone may be insufficient to establish 3 See also Johnson, 782 F. App’x at 281 (“[R]equiring a plaintiff’s statistics to be so detailed as to disprove any possible enforcement factor that a defendant may assert, even when there is no record evidence that any such factor exists, would mean that a plaintiff’s proof must be completely unassailable both factually and as a matter of law to even submit it to a jury.”). 8 Case 3:16-cv-00016-NKM-JCH Document 219 Filed 08/23/22 Page 9 of 14 Pageid#: 1377 causation … it is nonetheless relevant to identifying causal relationships.”). Defendants cite authority holding that, “[e]vidence of mere correlation, even a strong correlation, is often spurious and misleading when masqueraded as causal evidence, because it does not adequately account for other contributory variables.” United States v. Valencia, 600 F.3d 389, 425 (5th Cir. 2010). But Defendants’ brief omits the very next sentence of the opinion: “However where evidence of correlation itself is potentially relevant and unlikely to mislead the jury, an expert who reliably discerns this relationship can present such conclusions to the jury.” Id. (emphasis added). And indeed, in that case, the Fifth Circuit held that the district court did not abuse its discretion in admitting expert testimony about correlations, and the district court had recognized that the “defendants could highlight any inconsistencies on cross-examination,” id. at 425–26. The Fifth Circuit summed up that “[w]hether a particular opinion is relevant and reliable thus does not simply turn on whether the expert asserts a casual or correlative relationship, but is closely tied to the law and facts at issue in a given case.” Id. at 425 (citing Hodges v. Mack Trucks Inc., 474 F.3d 188, 195 (5th Cir. 2006)). At bottom, Defendants’ cited authority does not support their attempt to exclude Plaintiffs’ expert’s testimony. Indeed, far from attempting to “masquerade” evidence of correlation as causal evidence, Valencia, 600 F.3d at 425, Plaintiffs’ expert appears to candidly acknowledge the limitations of her statistical analysis in the portions of her deposition testimony cited by Defendants. See Dkt. 199 at 6–7; see also Dkt. 203 at 2. Nor is this a circumstance in which an expert has “failed to distinguish between ‘correlation’ and ‘causation.’” Verisign, Inc. v. XYZ.com LLC, 848 F.3d 292, 300–01 (4th Cir. 2017). Defendants also argue that Plaintiffs’ expert’s “calculations are irrelevant” because she “considered no factors or information other than race.” Dkt. 199 at 7; see also id. (“She did not 9 Case 3:16-cv-00016-NKM-JCH Document 219 Filed 08/23/22 Page 10 of 14 Pageid#: 1378 account for any other factors in the traffic stops conducted by the officers.”). This mirrors Defendants’ argument to the Fourth Circuit that Plaintiffs’ “statistics are insufficient because they are not detailed enough to exclude certain possible legitimate law enforcement factors that may explain the stark disparity in Holmes’s rate of traffic summonses for African American individuals.” Johnson, 782 F. App’x at 278. And, notably, the Fourth Circuit rejected that argument. The Fourth Circuit explained that such other potential variables were “speculative proposed factors” that “do not constitute ‘distinguishable legitimate enforcement factors,’” and “cannot justify excluding [Plaintiffs’] statistical evidence from proving discriminatory effect.” Id. at 280 (emphasis added). Defendants have not substantiated their argument to any greater degree in their briefing to this Court on this issue, though they had the opportunity to do so. Just as the Fourth Circuit rejected Defendants’ arguments that the statistics themselves should be excluded because other, unspecified variables or factors may undermine them, so too here, this Court rejects Defendants’ attempt to exclude Plaintiff’s expert testimony and calculations based on similar (and similarly unsubstantiated) assertions that other variables may undermine Plaintiffs’ expert’s opinion or calculations. Similarly, Defendants’ argument that Plaintiffs’ expert lacked sufficient data does not support excluding her opinion or calculations. Dkt. 199 at 7–8; Dkt. 210 at 2–3. This is another repackaged and repurposed argument that the Fourth Circuit already largely rejected. On appeal, Defendants similarly “fault[ed] [Plaintiffs’] statistical evidence for not revealing the reason each driver was stopped; whether a driver received more than one summons during the same stop; the specific types of offenses charged’ the specific location of the traffic stop within the sector; or whether the encounter involved a search.” Johnson, 782 F. App’x at 279. The Fourth Circuit explained that “the level of detail that Holmes seeks from [Plaintiffs’] statistics is fundamentally 10 Case 3:16-cv-00016-NKM-JCH Document 219 Filed 08/23/22 Page 11 of 14 Pageid#: 1379 at odds with the nature of aggregated data,” and that without some record evidence substantiating such factors and that those details would be material to Plaintiffs’ claims, the Fourth Circuit held that “missing information” did not warrant “excluding the statistics.” Id. There is more than a passing similarity between those arguments and some of those made here, including that the data used by Dr. Rovnyak “did not specify the type of offense,” or “whether it is the same individual or interaction resulting in the citation.” Dkt. 199 at 7–8. Defendants cite their own expert, saying that because the sample size of comparatorofficers to Mr. Holmes was small, “caution must be exercised,” and that having “more data” results in more accuracy. Id. at 8. That is fair. Caution must be exercised. The more data the better. Neither principle is or can be really in dispute. But neither principle warrants exclusion of the testimony and calculations on this record. Simply put, Defendants have not provided the Court any rationale to conclude that Plaintiffs’ expert’s opinion was lacking in sufficient facts and data such as would fall afoul of Fed. R. Evid. 702. Nor do Defendants’ arguments implicate several of the Daubert factors, namely, whether Plaintiffs’ expert’s technique has been tested or subjected to peer review or publication. See Kumho Tire, 526 U.S. at 149–50 (describing Daubert factors whether a “theory or technique … can be (and has been) tested,” and whether it “has been subjected to peer review and publication”). And, to the extent Defendants argue that Plaintiffs’ expert’s methodology had a high “known or potential rate of error,” or did not enjoy general acceptance within the relevant scientific community of statisticians, id. at 149–50, (Daubert factors); Dkt. 199 at 8–9, Defendants have not substantiated such arguments. Defendants have not demonstrated that any failure by Plaintiffs’ expert to conduct “standard tests” for “clustering” and “independence,” Dkt. 199 at 8–9, would so jeopardize the reliability of her methodology that would justify total exclusion of her testimony, such as would warrant a 11 Case 3:16-cv-00016-NKM-JCH Document 219 Filed 08/23/22 Page 12 of 14 Pageid#: 1380 conclusion that it was inadmissible, rather than merely subject to testing concerning the weight to be afforded such evidence. To be sure, the Fourth Circuit acknowledged that Defendant Holmes (and the other Defendants) “may raise his proposed enforcement factors, if true, before the jury to attack [Plaintiffs’] statistical evidence at trial.” Id. at 281. That remains the case. Indeed, Defendants would be “in the best position to know whether [their] proposed enforcement factors are true.” Id. at 280. However, following the Fourth Circuit’s opinion in Johnson v. Holmes, the potential existence of variables as those proposed enforcement factors do not warrant exclusion of the statistics or this testimony interpreting them at the outset. 4 Next, Defendants’ argument that Plaintiffs’ expert was not comparing “apples to apples” also fails. While it is true, as the Fourth Circuit explained, that “[t]he statistics must compare apples to apples,” Johnson, 782 F. App’x at 277, again, the Fourth Circuit also explained that 4 Defendants raise another argument in this same vein, that Plaintiffs’ expert’s “lack of subject matter knowledge compounds [her] faulty analysis.” Dkt. 210 at 4. In other words, they contend that because she is a mathematician and statistical consultant, with mostly prior work done in the healthcare field, she “has no relevant experience in law enforcement,” and “so she is not qualified to know whether or opine that she accounted for all the variables.” Dkt. 199 at 7; Dkt. 210 at 4. Significantly Defendants have not challenged Dr. Rovnyak’s qualifications to serve as an expert. See Dkt. 203 at 1–2. The Court also finds unpersuasive Defendants’ attempt to foist onto Plaintiffs’ expert sole responsibility for substantiating distinguishing enforcement factors, which Defendants themselves to date have not done—though, again, the Fourth Circuit wrote that they would be in the best position to do so, if any such distinguishment enforcement factors were true. Johnson, 782 F. App’x at 281. At argument, Defense counsel sketched out some bare, possible distinguishing enforcement factors they may attempt to raise at trial but had not done this yet. Nor did Defendants point to any distinguishing enforcement factor apparent on the face of the statistics or based on other record evidence Dr. Rovnyak failed to consider on account of her alleged lack of subject matter experience. See Dkt. 210 at 4–5. The Court does not consider Dr. Rovnyak to be attempting to testify, as Defendants argue, that “there are no other variables or underlying causes for which she should or could account or consider.” Id. at 4. In any event, any such points about whether Plaintiffs’ expert lacked important experience could, if anything, be brought out on cross-examination, but do not justify exclusion of the testimony entirely. 12 Case 3:16-cv-00016-NKM-JCH Document 219 Filed 08/23/22 Page 13 of 14 Pageid#: 1381 “none of Holmes’s proposed enforcement factors—that is, the five alleged statistical faults he raised—prevent [Plaintiffs’] statistical evidence from comparing apples to apples as a matter of law.” Id. at 278. And again, those “alleged statistical faults” included lack of certain “details” in the statistics, such as “whether a driver received more than one summons during the same stop,” or “the specific types of offenses charged.” Id. at 279. Defendants’ argument here does little more than repackage the same argument in a different posture, and as such, it will not preclude a jury from hearing Plaintiffs’ expert’s testimony. Lastly, this Court also considers the Fourth Circuit’s admonition that Plaintiffs have been forced to rely on Defendants for the statistical information to prove their claim, which is here (as on appeal), being challenged as inadequate by Defendants. Thus, “the very entity that decides what data to record is the same entity that would benefit from vague or incomplete statistics in selective enforcement cases like this one,” and that is a “reality” that this Court must take into account. See Johnson, 782 F. App’x at 284 (the district court on remand should “bear[ ] in mind the unique power imbalances inherent in selective enforcement cases when plaintiffs are forced to rely on the police department’s statistics to prove their claim”). This dynamic and the resulting motive that the Court avoid creating perverse incentives only further bolsters the Plaintiffs’ position—that Defendants’ arguments challenging Plaintiffs’ expert’s calculations on the statistics based on alleged deficiencies in the underlying data, which was produced by the County and Defendants’ police department, are evidentiary issues going to the weight of the evidence and not to its admissibility. Applying these principles, the Court concludes that the appropriate course is not for the Court to exclude Plaintiffs’ expert’s opinion entirely, but rather, to afford Defense counsel the regular means of challenging such testimony, as by cross-examination. See Daubert, 509 U.S. at 13 Case 3:16-cv-00016-NKM-JCH Document 219 Filed 08/23/22 Page 14 of 14 Pageid#: 1382 596 (citing the “traditional and appropriate means” of challenging expert testimony, including by “[v]igorous cross-examination, presentation of contrary evidence, and careful instruction on the burden of proof”). 5 Conclusion Accordingly, Defendants’ motion to exclude Plaintiffs’ expert Dr. Rovnyak’s testimony hereby is DENIED. Dkt. 198. It is so ORDERED. The Clerk of Court is directed to send a certified copy of this Memorandum Opinion and Order to all counsel of record. Entered this _____ 23rd day of August, 2022. 5 Defendants have cited Rule 403 as a basis for rejecting Plaintiffs’ expert testimony but have not expanded upon it. See Dkt. 198 at 2; Dkt. 199 at 2. In any event, the Court determines that allowing Plaintiffs’ expert’s testimony does not give rise to any unfair prejudice, much less such unfair prejudice as would substantially outweigh the probative value of the testimony. 14

Some case metadata and case summaries were written with the help of AI, which can produce inaccuracies. You should read the full case before relying on it for legal research purposes.

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.