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We contract with bar advocates and public defenders at a rate approved by Massachusetts' Committee on Public Counsel Services (CPCS).
- Many of these cases have involved the question of police bias, specifically racial profiling, as ruled upon in
- Comm. v. Lora, 451 Mass. 425 (2008),
- Comm. v. Long, 485 Mass. 711 (2020), and
- Comm. v. Robinson-Van Rader, 492 Mass. 1 (2023).
An invaluable resource." Attorney T. W., Boston, MA
Contact: Info@IntegrativeStatistics.com
Long, Daubert, & Acceptance of Methods
Statistical evidence with respect to police impartiality or bias has become pivotal to increasingly many criminal cases. In the tradition of Daubert v. Merrell Dow Pharmaceuticals, Inc., 509 U.S. 579 (1993), defense attorneys, prosecutors, and judges increasingly seek to evaluate the soundness, validity, or credibility of findings created by statistician-experts. This piece provides evaluation guidelines that apply especially to such cases and discusses pitfalls to avoid.
Statistical evidence with respect to police impartiality or bias has become pivotal to increasingly many criminal cases. In the tradition of Daubert v. Merrell Dow Pharmaceuticals, Inc., 509 U.S. 579 (1993), defense attorneys, prosecutors, and judges increasingly seek to evaluate the soundness, validity, or credibility of findings created by statistician-experts. This piece provides evaluation guidelines that apply especially to such cases and discusses pitfalls to avoid.
| long_daubert___acceptance_of_methods_-_roland_b_stark_-_sep._13_2023.pdf |
Impeccable testimony." Attorney S. Q., Holyoke, MA
Poor-Quality Official Data Impedes Justice in Racial-Bias Cases
(A version of this post was published as a letter to the editor in Massachusetts Lawyers Weekly,
in print Dec. 5, 2022. For online subscribers, https://masslawyersweekly.com/2022/12/02/letter-poor-quality-official-data-impedes-justice-in-racial-bias-cases/.)
Supreme Judicial Court decisions in Comm. v. Lora, 451 Mass. 425 (2008) and Comm. v. Long, 485 Mass. 711 (2020) may advance racial-justice efforts in Massachusetts. Both affirm that, to demonstrate potential bias in police officers’ treatment of criminal defendants, the accused can present statistical analysis of patterns of such treatment. However, the defense must rely on the state to compile accurate data for analysis.
State-provided data often turns out to be problematic.
As a statistician, I have repeatedly encountered serious deficiencies in traffic-stop data supplied by the Massachusetts State Police (MSP) and Department of Transportation (DOT). Some illustrative examples follow.
1. Wholesale inaccuracies in locations. One recent MSP data file covered 2,500 stops made by troopers assigned to Southeastern MA. Just 3% of the locations listed were in the Southeast. In another file containing wholesale errors, supposedly Truro was on Route 495, and Acushnet was a town in Texas. Last winter the MSP acknowledged “some errors” in their locations; I have seen no improvements since.
2. Missing data. For one set of officers, 40% of 1,000 citation decisions were blank. Those savvy about research know that simply using the data available risks introducing bias into the sample. Missing data also reduce sample size, often weakening analysis.
3. Implausible data.
Citations for certain offenses are omitted from the records. One data file describing 37,000 offenses included zero involving weapons -- even though corresponding police reports showed numerous weapons charges.
For one file, among 1,000 seatbelt citations 47% were the only citations listed for those drivers. Some seatbelt violations supposedly prompted a criminal charge or arrest. None of this is credible considering the secondary seatbelt-enforcement law.
4. Persistent unresponsiveness by the DOT and MSP to information requests. I have made repeated requests that the DOT explain unclear data elements. E.g., does “Search” apply to the vehicle only, or to driver or passenger? Besides “Y” and “N”, how to interpret blanks? No answers to these or any such questions have been received since January 2022. The MSP website invites data-related questions via email or web form. Submissions via both have produced no response since August 2022.
These defects are sure to interfere with prosecutors’ and police departments’ ability to conduct their own analyses, or to demonstrate equitable treatment of different groups. For the accused, far more than an inconvenience, this failure to generate accurate, transparent, usable data denies an important avenue of defense and thus a Constitutional right.
One cannot meaningfully test for over-representation of protected groups in traffic stops without being able to identify the area and thus the population patrolled.
Similarly, one cannot test for disparate treatment of those stopped without valid data on citations issued and for what offenses.
These deficiencies pose barriers to the kinds of defense not only permitted but encouraged by the Court in their Lora and Long decisions.
(A version of this post was published as a letter to the editor in Massachusetts Lawyers Weekly,
in print Dec. 5, 2022. For online subscribers, https://masslawyersweekly.com/2022/12/02/letter-poor-quality-official-data-impedes-justice-in-racial-bias-cases/.)
Supreme Judicial Court decisions in Comm. v. Lora, 451 Mass. 425 (2008) and Comm. v. Long, 485 Mass. 711 (2020) may advance racial-justice efforts in Massachusetts. Both affirm that, to demonstrate potential bias in police officers’ treatment of criminal defendants, the accused can present statistical analysis of patterns of such treatment. However, the defense must rely on the state to compile accurate data for analysis.
State-provided data often turns out to be problematic.
As a statistician, I have repeatedly encountered serious deficiencies in traffic-stop data supplied by the Massachusetts State Police (MSP) and Department of Transportation (DOT). Some illustrative examples follow.
1. Wholesale inaccuracies in locations. One recent MSP data file covered 2,500 stops made by troopers assigned to Southeastern MA. Just 3% of the locations listed were in the Southeast. In another file containing wholesale errors, supposedly Truro was on Route 495, and Acushnet was a town in Texas. Last winter the MSP acknowledged “some errors” in their locations; I have seen no improvements since.
2. Missing data. For one set of officers, 40% of 1,000 citation decisions were blank. Those savvy about research know that simply using the data available risks introducing bias into the sample. Missing data also reduce sample size, often weakening analysis.
3. Implausible data.
Citations for certain offenses are omitted from the records. One data file describing 37,000 offenses included zero involving weapons -- even though corresponding police reports showed numerous weapons charges.
For one file, among 1,000 seatbelt citations 47% were the only citations listed for those drivers. Some seatbelt violations supposedly prompted a criminal charge or arrest. None of this is credible considering the secondary seatbelt-enforcement law.
4. Persistent unresponsiveness by the DOT and MSP to information requests. I have made repeated requests that the DOT explain unclear data elements. E.g., does “Search” apply to the vehicle only, or to driver or passenger? Besides “Y” and “N”, how to interpret blanks? No answers to these or any such questions have been received since January 2022. The MSP website invites data-related questions via email or web form. Submissions via both have produced no response since August 2022.
These defects are sure to interfere with prosecutors’ and police departments’ ability to conduct their own analyses, or to demonstrate equitable treatment of different groups. For the accused, far more than an inconvenience, this failure to generate accurate, transparent, usable data denies an important avenue of defense and thus a Constitutional right.
One cannot meaningfully test for over-representation of protected groups in traffic stops without being able to identify the area and thus the population patrolled.
Similarly, one cannot test for disparate treatment of those stopped without valid data on citations issued and for what offenses.
These deficiencies pose barriers to the kinds of defense not only permitted but encouraged by the Court in their Lora and Long decisions.
Contact Roland Stark. He works very hard and is easy to communicate with. He has great ideas and makes me smarter every time we speak." Attorney N. W., Norfolk County, MA
Contact: Info@IntegrativeStatistics.com
Critique of Report on Auto Stops and Race in MA
This short .pdf piece explains why statistical errors undermine confidence in the report published by Salem State University and Worcester State University, February 7, 2022. Their anonymous report presumes to show whether racial bias occurs, either in police decisions about which motorists to stop or in which types of citations to issue to the drivers stopped. Their report was disseminated by the MA Executive Office of Public Safety and Security (EOPSS), apparently without any vetting as to the soundness of the methods used.
(A condensed version of this critique was published as a letter to the editor of Mass. Lawyers Weekly, April 8, 2022. For online subscribers, https://masslawyersweekly.com/2022/04/08/letter-statistician-points-to-shortcomings-in-traffic-stop-report/.)
This short .pdf piece explains why statistical errors undermine confidence in the report published by Salem State University and Worcester State University, February 7, 2022. Their anonymous report presumes to show whether racial bias occurs, either in police decisions about which motorists to stop or in which types of citations to issue to the drivers stopped. Their report was disseminated by the MA Executive Office of Public Safety and Security (EOPSS), apparently without any vetting as to the soundness of the methods used.
(A condensed version of this critique was published as a letter to the editor of Mass. Lawyers Weekly, April 8, 2022. For online subscribers, https://masslawyersweekly.com/2022/04/08/letter-statistician-points-to-shortcomings-in-traffic-stop-report/.)
Analyzing for Bias in Traffic-Stop Cases: Video Presentations
Each of the videos below explains an aspect of analyzing for bias or racial profiling in police stops.
Each video is 3-7 minutes long. Each assumes no prior statistical background.
(Last updated Nov. 7, 2022.)
Session 1. How might we assess, statistically, whether a pattern of law enforcement is biased?
Session 2. What to expect from official MA data on police stops
Session 3. Statistical Significance: Concepts
Session 4. Statistical Significance: Choosing a Threshold
Session 5. Controlling for Many Factors