# Driving While Black/Driving While Brown?

Introduction

The purpose of this project is to investigate racial profiling, or Driving While Black or Driving While Brown (DWB/DWB). African Americans and Latinos/as have complained, filed suit, and organized against what they believe are racist police practices—being stopped, searched, harassed, and arrested because they “fit” a racial profile—they are African American (Black) or Latino/a (Brown). But is this true? How do we know? And can mathematics be a useful tool in helping us answer this question?

SUBJECT: Mathematics

NUMBER OF DAYS LONG: 3-5

MATH TOPIC: Data analysis (collecting, analyzing data); Probability (simulations, law of large numbers, theoretical/experimental probabilities)

SOCIALJUSTICE TOPIC: Racial profiling

TOPIC OBJECTIVE

Students learn: (a) how to analyze data collected from a probability simulation; (b) how to set up their own simulation; (c) about the law of large numbers; (d) about the relationship of theoretical probabilities and empirical data.

SOCIAL JUSTICE OBJECTIVE

Students use mathematics to analyze racial profiling data and compare actual data to results of a probability simulation about racial profiling. This then becomes an entry point into a discussion about whether racial profiling is a real issue, is racism a factor, why does it occur, and if it’s a problem, what can one do about it.

INTRODUCTION TO THIS REAL ISSUE

DRUG TRAFFICKERS ARE NOT “MOSTLY MINORITIES”

Racial profiling is based on the premise that most drug offenses are committed by minorities. The premise is factually untrue, but it has nonetheless become a self-fulfilling prophecy. Because police look for drugs primarily among African Americans and Latinos, they find a disproportionate number of them with contraband. Therefore, more minorities are arrested, prosecuted, convicted, and jailed, thus reinforcing the perception that drug trafficking is primarily a minority activity. This perception creates the profile that results in more stops of minority drivers. At the same time, white drivers receive far less police attention, many of the drug dealers and possessors among them go unapprehended, and the perception that whites commit fewer drug offenses than minorities is perpetuated. And so the cycle continues.

This vicious cycle carries with it profound personal and societal costs. It is both symptomatic and symbolic of larger problems at the intersection of race and the criminal justice system. It results in the persecution of innocent people based on their skin color. It has a corrosive effect on the legitimacy of the entire justice system. It deters people of color from cooperating with the police in criminal investigations. And in the courtroom, it causes jurors of all races and ethnicities to doubt the testimony of police officers when they serve as witnesses, making criminal cases more difficult to win.

When we make a stop, it’s not based on race or gender or anything of that nature. It’s based on probable cause that some law is being broken, whether it’s traffic or otherwise. We have to have a reason.”
– Lincoln Hampton, spokesman for the Illinois State Police (Chicago Tribune 4/4/99)

Hello students.

This unit has two parts. Please, is very important that you do all proposed activities in both math (part 1) and social justice (part 2) to understand the main topic of this unit and achieve the given goals.

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PART I. Review basic probability ideas and Racial Profiling.

To understand about racial profiling, it is need you understand several math concepts such as: randomness, experiment, simulation, sample size, experimental and theoretical probability, and the law of law numbers (i.e., the more experiments you run, the closer you come to theoretical probabilities). I invite you to watch the following videos:

Probability and Statistics | Khan Academy:

Introduction to Probability, Basic Overview

Racism Profiling

To determine whether a police department engages in illicit racial profiling, courts look at metrics such as how often people of color are subjected to stops and searches relative to their portion of the population; whether searches frequently turn up contraband; and how often stops lead to an arrest or charges. Litigants must generally compile a significant body of statistical and anecdotal evidence to prevail in a profiling case.

Also, I invite you to read the following document about racial profiling: https://www.ojp.gov/pdffiles1/bja/184768.pdf

Process

Let's Practice Together: One way to begin discussing these ideas is to have pairs of students toss a coin 100 times (the experiment) and record results, then combine the class data and have the whole class together examine how the combined data comes closer to a 50-50 split than do the individual pairs (the law of large numbers).

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PART II. Find Chicago’s racial breakdown. Give each group of students a small bag with colored cubes to match the racial breakdown. I used 9 black (African Americans), 9 tan (whites), 6 reds (Latinos/as), and 1 yellow (Asians/Native Americans) to approximate Chicago racial proportions. Do not tell students the total number of cubes nor how many of each color. Students pick one cube without looking, record its color, and replace the cube. They record the results of each 10 picks in the chart below (tally marks work well). Each line in the chart below is the cumulative total of picks. Tell students that they are conducting an experiment (picking/replacing 100 times), collecting data (recording each pick), and analyzing data (determining from their simulation, how many there are of each color, and the total, and what are the Chicago racial/ethnic percents.

Make sure students record the fraction and percentage of each race/ethnicity for every 10 picks in the chart.

 # of picks White # White fract. White % AfAm # AfAm fract. AfAm % Latino # Latino fract. Latino % Asian # Asian % Asian fract. 10 20 30 40 50 60 70 80 90 100 Total

Questions for each group. Emphasize thorough written explanations for all questions.

1) Without opening up the bag, how many cubes of each color do you think are in it? WHY???

2) What happened as you picked more times, and what you think will happen if you pick 1,000 times?

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PART III

Investigating DWB/DWB.

Here are sample Illinois data based on police reports from 1987-1997. In an area of about 1,000,000 motorists, approximately 28,000 were Latinos/as. Over a certain period of time, state police made 14,750 discretionary traffic stops (e.g., if a driver changes lanes without signaling, or drives 1-5 mph over the speed limit, police may stop her or him but do not have to). Of these stops, 3,100 were of Latino/a drivers.

You will allow to they are able to apply what they learned in Part II and set up their own simulation of the situation using cubes (you may will need more cubes, but you can let them figure this out. In my class, they either used 3 different-colored cubes of 100, or 1 of 36—this part is very difficult!). Have them pick and replace, record the data, and calculate the results of simulating 100 “discretionary” stops.

More group questions:

3) What percentage of the motorists in Part III were Latino/a?

4) What percentage of the discretionary traffic stops were Latino/a?

5) How did you set up the simulation for problem #3 (how many “Latino/a” cubes and how many total?)? Why did you choose those numbers?

6) How many Latinos/as were picked out of 100 picks, and what percentage is that?

7) Do your results from your simulation experiment (#6) support the claim of racial profiling? Why or why not?

Combine individual groups’ results and analyze as a whole class.

Evaluation

You will be graded according to the rubric below. Be creative and do your best! I hope you learned a lot!

Make sure that you share through google or email all of your work!

 Criteria Level 1 Level 2 Level 3 Level 4 Knowledge/understanding - demonstrates limited knowledge of mathematical terms (probability tree; reading a spinner to get information - demonstrates limited understanding of the probability of events occurring (e.g. 3 in 6 chances of rolling an even on a die) - demonstrates some knowledge of mathematical terms (probability tree; reading a spinner to get information - demonstrates some understanding of the probability of events occurring (e.g. 3 in 6 chances of rolling an even on a die) - demonstrates knowledge of mathematical terms (probability tree; reading a spinner to get information - demonstrates understanding of the probability of events occurring (e.g. 3 in 6 chances of rolling an even on a die) - demonstrates thorough knowledge of mathematical terms (probability tree; reading a spinner to get information - demonstrates through understanding of the probability of events occurring (e.g. 3 in 6 chances of rolling an even on a die) Thinking - uses processing skills with limited effectiveness - uses planning skills with limited effectiveness - uses processing skills with some effectiveness - uses planning skills with some effectiveness - uses processing skills with considerable effectiveness - uses planning skills with considerable effectiveness - uses processing skills with high degree of effectiveness - uses planning skills with high degree of effectiveness Application - applies math knowledge and skills with limited effectiveness to understand / figure out cultural issues such as racial profiling - transfers knowledge and skills to new contexts with limited effectiveness - applies math knowledge and skills with some effectiveness to understand / figure out cultural issues such as racial profiling - transfers knowledge and skills to new contexts with some effectiveness - applies math knowledge and skills with considerable effectiveness to understand / figure out cultural issues such as racial profiling - transfers knowledge and skills to new contexts with considerable effectiveness - applies math knowledge and skills with high degree of effectiveness to understand / figure out cultural issues such as racial profiling - transfers knowledge and skills to new contexts with high degree of effectiveness

Conclusion

INDIVIDUAL WRITEUP

1. What did you learn from this activity?

3. Do you think racial profiling is a problem, and if so, what do you think should be done about it?

4. What questions does this project raise in your mind?

Credits

Mathematics Standards:

MP.2 Reason abstractly and quantitatively. Students understand that the outcomes in probability situations can be viewed as random variables—that is, functions of the outcomes of a random process, with associated probabilities attached to possible values.

MP.4 Model with mathematics. Students apply their new mathematical understanding to real-world problems. They also discover mathematics through experimentation and by examining patterns in data from real-world contexts.

Use data from a sample survey to estimate a population mean or proportion; develop a margin of error
through the use of simulation models for random sampling.

NETS- Students- Communication and Collaboration.

Students use digital media and environments to communicate and work collaboratively, including at a distance, to support individual learning and contribute to the learning of others.
a. Interact, collaborate, and publish with peers, experts, or others employing a variety of digital environments and media.
b.Communicate information and ideas effectively to multiple audiences using a variety of media and formats.
d.contribute to project teams to produce original works or solve problems.

Credits / Reference list.

This Unit was taken and modified from: http://www.teachersforjustice.org/2010/01/mathdriving-while-blackdriving-while.html

This Unit was modified by Fabio A. Ortiz. (I am a teacher and I took this unit faithfully respecting its authorship, only some modifications were made to complement the activities and enrich the proposed learning objectives.)

I was able to get all of my pictures from Google images.