Apply Critical Thinking!

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Harassment?

A recent blog on Facebook mentioned 16% of those ticketed for jaywalking in their community were of one race.  The racial percentage of that group in the community was only 10%. Comments on Facebook included a few that assumed the cause of this gap was police racial bias leading to unfair ticketing (harassment). 

Critical Thinking Approach

Our approach to understanding an unexpected or undesirable observation is to evaluate potential causes using the known facts. While admitting that this type of issue can stir up wounds and memories of abuse, anger and injustices, we want to step back and prescribe how to analyze the situation. That’s our business. We teach critical thinking. Our experience has been that problems only get worse without an accurate under-standing of the precipitating causes.  In this example:

“Why does this ethnic group receive 16% of the jay walking tickets?”

Purpose

Imagine we are a group given authority and responsibility to monitor and eliminate racial bias in policing.  We define racial bias in this context as enforcement behavior differentially applied between racial groups including these categories of police actions:

1. Observe and ticket.
2. Observe and give warning.
3. Ignore an infraction – fail to act.
4. Fabricate an infraction.
5. Police-Suspect Interaction Issues (physical, verbal, type of restraint, use of force)

Policing – Stated Objectives

1.  JUSTICE – Only violators to be ticketed.
2.  FAIRNESS – No violator will be ticketed or not ticketed based upon race.
3.  ACCURACY – Obtain accurate assessment of any race-biased enforcement.
4.  QUALITY OF LIFE – seek to make the community more safe, pleasant, just, and agreeable to all residents.
5. IMPROVE RELATIONSHIP between police and each part of the community (all races, all people, and institutions).

Big Picture

It is common for people to jump to conclusions and recommend a solution to a “problem” based solely upon assumptions about what is happening.  Therefore, we want to start not with a solution, but with an analysis that verifies the true cause.

Why? Knowing the cause is likely to obtain better results including not making the problem worse and/or causing new problems.

QUOTAS.  For example, the imposition of quotas has become a common solution to racial bias.  This shifts the focus away from bias and onto a number.  Then someone can hide bias by manipulating the number(s). 

An analogy: Suppose your doctor took your temperature and the reading was verified at 104F degrees.  Or, what if he cooled the (old) thermometer two 40F degrees before using it to measure your temperature?  That could result in a lower temperature reading [due to not having enough time to read the body’s temperature].  You are still sick as before, but the measure may not reveal it.

Quotas are open to different manipulations.  The biased organization may attempt to work on the numbers and not the cause of the numbers.  This can easily result in sacrificing justice, fairness and accuracy.  What if police leaders monitor the numbers and then issue targets to level them and to hide bias.  “Today, no jay-walking citations for ethnic group A.  Give tickets to ethnic group B only.”  What’s wrong with that?  It sends the wrong message to law breakers.  Demoralizes police and makes a sham of the oaths they’ve taken to enforce the laws of the city. The numbers do not represent truth, just hides it.

Quotas can be a last ditch effort to improve fairness, but they are far from an ideal solution – we think.  The A group will learn that they can flaunt the laws.  And more serious violations may follow from them.  The community is not stupid.  Many will see the police failing to do their job.  The A group will get a bad reputation as privileged, and resentment will grow all around.

Gathering relevant facts helps develop quality potential causes.  Evaluation consists in finding the best fit of a potential cause to the available facts. The better the facts fit a potential cause the more likely it is to be the true cause.  And, then it is worth trying to verify.

DOES THE BIAS HYPOTHESIS FIT THE FACTS?

Let’s assume for the moment that we think the true cause of 16%/10% observation is police racial bias! What facts would we expect to find in answer to the questions below?

1. Review street camera recordings.  What is the total number of violations recorded by race before the police get involved. (Expect the A group does not show more jaywalking than other groups.)
2. What is the full community distribution by race in relation to J-tickets? (Expect no other ticket anomalies with other races.)
3. What other characteristics do those being ticketed have, like gang membership, age, history of violations, police identified Persons Of Interest in more serious violations? Relationships in the neighborhood? (Expect no distinguishing differences in other characteristics found for those ticketed in A group.)
4. What is the ethnicity of the police officers issuing the tickets. (Expect mismatch of police to suspect race.)
5. How many people given tickets were previously known to the police officer issuing the ticket (Expect no pattern of previous relationship between ticketing officers and specific jaywalkers)
6. What valence in terms of mutual respect existed? (We’d expect a relationship that was neutral on average).
7. What was the larger imposed goal for policing by management? How was the big picture framed for the officers by their superiors. (E.g., No announced curfew program; or goal of breaking up groups of youth on the street.).
8. Were there complaints about jaywalking from residents and its impact? (Expect no unusual number of complaints about blocking traffic, accidents, or rowdiness complaints from neighbors blaming jaywalkers).
9. Volume of foot traffic by race (Expect no more people of this race on foot in the community than their percentage of population).
10. Day, Location, Time and traffic conditions can influence police activity. (Expect no patterns in the environment resulting in more police in the area.)
11. Are there certain officers who hand out more-tickets to this race than fellow officers? (Expect no officer to stand-out in # of tickets issued).

MOST LIKELY CAUSE? Fast forward. Did the available supplemental facts fit the bias theory? Whatever potential cause fits the facts best needs to be tested to verify if it is the right one.

TEST. If bias is the most likely cause, we must TEST that theory. Maybe have a number of different race small groups Jaywalk in the area and see if the police ticket unequally.

SOLUTION?

One cannot prescribe a great cure without knowing what the real cause(s) are. And the cause today may not be the cause long ago or in the future.  Only when you verify the true cause can one get an effective corrective action. And above all keep clear on your purpose. Is improving the health, safety and fairness in our community the goal? Great. Count me in.

[I agree with those who say that a Jay-ticket argument may not be about Jaywalking. Like arguments with one’s spouse, what your spouse says is upsetting them may not be what they are upset about. So don’t argue first.  Everyone must first listen!]