State of Texas Racial Profiling Definition

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State of Texas Racial Profiling Definition

• A law enforcement initiated action based on
  an individuals race, ethnicity, or national
  origin rather than on the individuals behavior
  or on information identifying the individual as
  having engaged in criminal activity.

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Vitae John C. Lamberth, Ph.D.

• Ph.D. from Purdue University.
• Associate Professor of Psychology, Temple
  University (Philadelphia).
• Co-founder of Lamberth Consulting, LLC.
• Consultant and Expert Testimony in State and
  Federal Courts.
• Numerous publications and papers on topics of
  Social Psychology, Jury Selection, and Racial
  Profiling.

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RACIAL PROFILING DATA ANALYSIS STUDY
Final Report for the San Antonio Police
Department
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Lamberth Consulting

• What we do
• Help law enforcement agencies proactively address
  racial profiling and issues of biased policing
• How we do it
• Provide stop data analysis and training solutions

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LC Sample Client List

• Grand Rapids PD, MI
• Washtenaw County SD, MI
• Ann Arbor PD, MI
• Newark PD, NJ
• Redlands PD, CA
• Overland Park PD, KS
• Kansas City PD, KS
• Wichita PD, KS
• Kansas Highway Patrol
• Olathe PD, KS
• Park City PD, KS
• Emporia PD, KS
• Hutchinson PD, KS
• Mont. County PD, MD

• Washington, DC PD
• New Jersey, PDO
• ACLU, Maryland Office
• ACLU, Michigan
• ACLU, CA
• ACLU, OK
• Dutchess County, NY
• Seattle WA, PDO
• Coconino County, PDO
• Marysville PD, KS
• Osage County SD, KS
• Mishawaka PD, IN
• Santa Cruz County, CA
• San Antonio PD, TX

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Proactive Approach

• San Antonio takes leadership role
• Proactively addressing racial profiling, in
  contrast to many agencies responding after
  litigation or decree
• Surpassing State Legislature requirements

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Benefits of Proactive Approach

• Service oriented
• Enhance police-community relations
• Measurement vs. anecdotal data

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San Antonio Data Analysis

• Stop Data taken from 2002 Traffic Stops
• Benchmarks An important role
• Possible benchmarks
• Census
• Accidents
• Traffic

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Why We Dont Use Census

• Census Underestimates 36 times
• Census Overestimates 42 times
• Range 64 overestimated (Harry Wurzbach I 410)
  to 600 underestimated (Basse US 281)

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Traffic vs. Census Data

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Traffic vs. Census Contd

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Lamberth Consulting Methodology

• The methodology that was utilized to analyze San
  Antonio Police Department racial profiling data.

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Planning Phase

• Agency reviews methodology and timeline
• Community group identified and begins review
  process
• Periodic status meetings

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Developing Benchmarks

• Review stop data with SAPD
• Locations (intersections) identified
• Site visits conducted to determine practicality

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Benchmarks Contd

• Locations reviewed and finalized
• Survey teams conduct surveys at designated
  locations
• Visual identification and manual recording of
  drivers race and ethnicity
• Days and times for surveying randomly selected

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Locations and Perimeters

• Perimeters were drawn around each location
• Stops within perimeters were compared to
  benchmarks

Benchmark Location
Location Perimeter
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39 Locations

• I- 10 Fresno
• S.W. Military Tacoma S.W. Military
  Pleasanton
• S.W. Military Zarzamora
• Guadalupe S. Zarzamora
• Wheatley Courts
• Lombrano Hamilton
• Commerce Presa
• I-410 Marbach
• San Pedro Cypress
• Loehmans Village
• I-10 Hildebrand
• I-35 US 90

• I-410 Perrin Beitel
• I-10 Woodlawn
• I-410 Broadway
• I-10 Wurzbach
• Market Bowie
• US 281 I-35
• US 281 N. St. Marys
• I-410 Ingram
• US 281 Hildebrand
• I-10 Medical
• I-410 Starcrest
• Pin Oak Oaklawn

 
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Locations Contd

• I-10 Vance Jackson
• Broadway Mulberry
• US 281 Basse
• I-35 Walzem
• Commerce Main Plaza
• W. Commerce Gen. McMullen
• I-410 N.E. US 281
• I-410 Culebra
• North Star Mall
• I-410 Harry Wurzbach
• I-10 West

• I-10 DeZavala
• I-10 Fredericksburg
• W. Military US 90
• I-37 New Braunfels

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The 39 Locations
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Data Analysis

• Survey data, or benchmark data, is then compared
  against the stop data
• By location
• Separate analyses for Black and Hispanic motorists

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Analysis Contd

• Odds-ratio
• If you are Black (Hispanic) you are ___ times as
  likely to be stopped as if you are not Black
  (Hispanic).

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What Does It Mean?

• Odds-ratio Analysis for Black Motorists
• 1.0 1.5 Benign
• 1.6 2.0 Review of stops recommended
• 2.0 Review of stops required
• Odds-ratio Analysis for Hispanic Motorists
• 1.0 - 1.7 Benign
• 1.7 2.2 Review of stops recommended
• 2.2 Review of stops required

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Race Analysis

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Race Analysis Contd
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Race Analysis Summaryfor the 39 Locations

• 8 Locations ? 1.0
• 13 Locations 1.0 1.5
• 14 Locations 1.6 2.0
• 4 Locations ? 2.0
• Overall 1.3

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Ethnicity Analysis
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Ethnicity Analysis Contd
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Ethnicity Analysis Summaryfor the 39 Locations

• 13 Locations ? 1.0
• 18 Locations 1.0 1.7
• 6 Locations 1.8 2.2
• 2 Locations 2.2
• Overall 1.2

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Odds Ratios - Black Motorists

• Overall odds ratio of 1.3 good! ?
• Review odds ratios over 2
• Lombrano Hamilton, 3.3 odds ratio -
  Recreational center working on reduced summer
  hours during benchmarking
• Broadway Mulberry, 2.8 odds ratio - Focal point
  of activity closed during benchmarking

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Odds Ratios - Hispanic Motorists

• Overall odds ratio of 1.2 good! ?
• 2 areas to review
• North Star Mall with an odds ratio of 3.1
• 58 of suspects were Hispanic
• W. Military US 90 with an odds ratio of 2.4

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Searches

• Use of higher discretion searches in determining
  whether minorities are over- searched
• No standard benchmark for proportion of minority
  searches
• Definitive evaluation more difficult

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Race and Ethnicity by Search Category
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Consensual Searches

• Consensual searches of Black motorists seems high
• 3 reasons to question the disparity
• More officer deployment in the East District
• Directed Patrols in high crime areas
• Higher likelihood of individuals on probation or
  parole being asked for consent to search

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Conclusions

• Some of the best results we have seen in the
  country
• The few disparities are not as large as in other
  studies
• Agency commended on proactive approach, results
  and commitment going forward

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Recommendations

• Continue collecting stop data
• Make changes in their data collection to
• Note criminal record
• Indicate a request for a consent search
• Indicate third party information stop
• Monitor those high odds-ratio locations

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Recommendations Contd

• Consider officer training specifically oriented
  to racial profiling
• Continue to work closely with the community group
• Encourage officers to call in more traffic stops