Author: dev@wilmingtondesignco.com

Recruiting Cops Who Will Stay

Posted on by dev@wilmingtondesignco.com

Law enforcement agencies invest a great deal of time and money into each individual they hire as a law enforcement officer. As a result, having the ability to identify individuals who are likely to voluntarily resign their employment after a few years or even months would be extremely useful. If it were possible to identify such individuals before a hiring offer was made, it could help law enforcement agencies retain more officers and avoid wasting resources on people who are likely to leave around the time that they become effective officers. We examined this issue with the data from our DCG Police Recruiting and Hiring Survey to see if there were detectable differences between the officers most likely and least likely to stay with their current agency.

The Sample

Sworn law enforcement officers who attended the various training courses offered by the Dolan Consulting Group (DCG) from August 2018 through March 2019 were given the opportunity to participate in our DCG Police Recruiting and Hiring Survey. A total of 1,673 sworn personnel took the survey. Included in this survey were four questions that measured the respondents’ likelihood of staying with, or resigning from, their current law enforcement agency within the near future. These questions asked the respondents how strongly they agreed or disagreed with the following statements.

I am making an effort to find a new job with another employer within the next year.

I am actively looking for a job with other employers.

I plan to voluntarily quit my job soon.

I frequently think about ending my employment with this department.

Being of a sensitive nature, 15% of the respondents did not answer one or more of these questions. Another 29% of the respondents indicated that they had more than 20 years of career service, making them likely eligible for retirement if they chose to retire soon. We excluded these individuals to examine only those who both answered all the questions about quitting soon and had less than 20 years of service with their department.

We then examined the respondents’ likelihood of quitting soon by adding their scores from these four quitting statements, with responses of strongly disagree = 1 and strongly agree = 5. Approximately a third of the remaining participants had the lowest score possible (4 points), indicating they responded strongly disagree to all four of these statements about leaving. This group of 298 respondents was the third of the sample most likely to stay and least likely to leave before retirement. Approximately another third of the respondents (326 individuals) scored 10 or higher on this scale of likelihood of leaving, making them the group most likely to leave before reaching retirement. We eliminated the middle third of respondents and then compared just the responses of the two extremes—the third most likely to leave and the third most likely to stay— to see if they were drawn to their careers or employers for different reasons.

Reasons for Selecting this Career

Both groups—those most likely to stay and those most likely to quit—were primarily drawn to the law enforcement career by a desire to help people, do interesting work, and through personal invitations to join the profession made by current law enforcement officers. Some notable differences, however, were revealed between these two groups. These four differences are displayed in Table 1 below. 

The greatest difference between those most and least likely to quit their departments in the short term was the influence of having seen and interacted with the police working in their community. Two-thirds of those most likely to stay with their department had this experience while growing up, while only one third of those quitting had this experience.

Somewhat related to this is the fact that about 2 out of every 10 officers staying were drawn to the career by popular media portrayals of the police, while almost 4 out of every 10 officers quitting were drawn by popular media images. Those most likely to be quitting were also almost twice as likely to be swayed to pursue the career because of television or internet advertising. 

These differences suggest that those staying had greater exposure and influence from seeing real law enforcement officers engaging in real police work, while those quitting were influenced more by the unrealistic portrayals of police work found within popular media. Obviously, those drawn to the career by seeing real examples of what the job entails would be less disillusioned than individuals drawn to the career by false media images of the career.

Table 1. Differences in Reasons for Selecting this Career

Another important difference between these two groups was the perceived lack of other career alternatives. Those most likely to quit were almost five times more likely to have said a lack of other job opportunities led them to pursue a law enforcement career. This strongly suggests that law enforcement was not their first career choice and not their life’s passion. A law enforcement career is very noble and rewarding, but it is also fraught with stress, frustration and danger. It should not be surprising that those who entered the law enforcement profession simply because they needed a steady job would be at much greater risk of quitting in the short term.

When screening applicants in oral review boards or written tests, agencies should consider examining these issues by asking the applicants pointed questions. What exposure does the applicant have to real police work? What does the applicant think a typical day of police work entails? What other career options does the applicant have? How long has the applicant wanted to be a law enforcement officer? Would the applicant still do the job if he or she had to take a pay cut? Law enforcement agencies should consider including a ride-along (or two or three) as part of the selection process so that the applicants can see the job firsthand. These findings also highlight the value of cadet, auxiliary, and reserve officer programs that allow potential future applicants to see the job firsthand and demonstrate their commitment to the profession by volunteering to participate without pay.

Reasons for Selecting their Specific Agency

Next, these two groups (quitting and staying) were compared to see if differences existed in why they chose to apply to, and accept employment with, their respective law enforcement agencies. Both those most and least likely to quit were drawn to their employing agencies by the pay, benefits package, and retirement plan. Beyond that, key differences were again revealed between these two groups with regard to what led them to their current employing agencies. These differences are displayed in Table 2 below.

Table 2. Differences in Reasons for Applying to this Particular Agency

Two important trends are revealed in Table 2. First, those most likely to stay were more likely to be drawn by the specific characteristics of their employing agency and community. Compared to those most likely to quit soon, those most likely to stay were more attracted to their department’s professional reputation and prestige, size, career opportunities, excitement level, and the safety level of where they could live. Please keep in mind that these respondents come from agencies and communities of all sizes. This means that those who are most likely to stay found the size, workload, and community of their agency to be a good fit for them. Those most likely to leave apparently did not place much importance on these fundamental aspects of the agency when applying to their departments and accepting the job offer. 

The second important trend revealed by Table 2 is the fact that those most likely to quit perceived they had few other employment options and just took the first (or only) law enforcement job offer to come along. Compared to those most likely to stay, those most likely to quit soon were 33% more likely to agree with the statement, “I was attracted to my current employer because this was the first agency to offer me a job.” Also, those most likely to quit were four times more likely to agree with the statement, “I was attracted to my current employer because I lacked other job offers or opportunities at the time.” A law enforcement career is so demanding, and officers have so much authority and responsibility in the course of their duties, that we should not be hiring people as officers who are interested in the position as a last resort.

When screening applicants, law enforcement agencies should consider examining these two areas during their interviews as well. Ask applicants about the other employment prospects they might have – inside or outside of law enforcement. Ask applicants to specifically describe what attracted them to apply to your agency. Ask applicants what experiences they want out of their law enforcement career. Do they want to someday be a detective or a member of a specialized unit? There is nothing wrong with these career goals if your agency is large. If your agency is small, with few opportunities for specialty assignments, then this applicant has the potential to become a future disgruntled employee. It is important that you hire individuals who fit your agency’s size and culture. Furthermore, it is important that you avoid hiring people who have no better career options. There are probably very good reasons, linked to the applicant’s skills, attitudes, and behaviors, for why this applicant has few other career options.

Conclusion

In summary, it appears that there are some notable differences between those who are most or least likely to stay with your agency—differences that can be detected at the pre-employment stage. Those most likely to stay with your agency in the long term are more likely to have entered the career with a realistic view about the occupation—a view developed from seeing the job firsthand. Those most likely to quit the job in the short term are more likely to have entered the career with a false, entertainment media image of police work, thus becoming dissatisfied when the career was not what they had expected.

Those most likely to stay with your agency in the long term are more likely to have chosen a law enforcement career from several potential career options available to them. Those most likely to quit the job in the short term are more likely to have entered the career with fewer other employment options.

In short, people who stay chose a law enforcement career because they wanted to do so, and those who leave chose the career because they had few other options. Those most likely to stay with your agency in the long term are more likely to have selected employment with an agency that best fit their personality and career desires, while those most likely to quit gave less thought to the reputation, size, workload, or culture of their employing agency. Finally, those most likely to quit in the short term were more likely to just need a job—any job.

About the Authors

Dr. Richard Johnson serves as Chief Academic Officer for Dolan Consulting Group. In that capacity, he acts as the lead researcher in conducting DCG Recruiting and Retention Surveys throughout the United States.

Attorney Matt Dolan serves as Director for Dolan Consulting Group. He conducts training courses throughout the United States on the various topics, including Recruiting and Hiring for Law Enforcement.

Racial Profiling or Bad Research? Why We Should Stop Using Census Data

Posted on by dev@wilmingtondesignco.com

Public opinion surveys reveal that the vast majority of Americans believe that use of racial profiling by the police is widespread.[1] This is deeply disturbing for two reasons. First, it is disturbing because it undermines police legitimacy among the vast majority of our citizens. Second, it is disturbing because the vast majority of law enforcement officers I have known do not engage in bias-based policing. This begs the question, then, why do so many people perceive that racial profiling is widespread?

One major factor that has contributed to the problem is the fundamentally flawed research that has been given the public through traffic stop data reports that have gathered and reported the wrong data. Many law enforcement agencies gather data on the race and gender of the individuals their officers have stopped, and report these data to the public in a report issued by the agency or by the state attorney general. Often these reports have relied on faulty methodologies that have been rejected by academics for decades, but still continue to be used.

The most common error found in these reports is the use of Census data as the benchmark for comparing the racial makeup of the jurisdiction to the racial makeup of those drivers stopped by the police. When people get into their car they do not limit their travels to their city limits and Census data does not demonstrate who is on the road or who is committing traffic violations.

Benchmarks

In order for any traffic stop data collection activity to be meaningful, the racial composition of drivers stopped by the police needs to be compared to something – a benchmark. A benchmark is generally defined as a point of reference from which measurements may be made; something that serves as a standard by which others may be measured or judged. In the context of traffic stop data collection, a benchmark is the percentage of a racial or gender group that one would expect to be encountered if officers were not biased.

For example, imagine that 20% of the people speeding down a particular stretch of roadway were male and Hispanic. This makes 20% our benchmark for speeding stops of male Hispanics. We would expect that unbiased stops by police for speeding in this area would show that only about 20% of those stopped for speeding were male Hispanic drivers. However, where do we get these benchmarks? Unfortunately, many law enforcement agencies, government officials, the news media, and citizen groups continue to use Census data – a fatally flawed benchmark.

Census Data

The U.S. Census Bureau collects data on the social and demographic characteristics of the individuals who live within the U.S. at a given point in time. This data is freely and easily accessible from the U.S. Census Bureau website and can be analyzed within different geographic regions, down to the zip code and Census block levels. Many have used Census data as their benchmark for police activity because of its ease of access. The problem, however, is that that the demographic characteristics of the people living at any one location at ten year intervals has nothing to do with the driving population in a given place, nor who is breaking the law in any specific area. We use our vehicles to travel to places away from our homes, as people generally do not work, shop, or recreate in their homes. Several studies illustrate this well.

Sociologists Albert Meehan and Michael Ponder, from Oakland University, examined the racial composition of drivers across one suburb in the Detroit Metropolitan Area. According to the U.S. Census, the suburb they studied had a population that was 3% African-American, but the city also contained a popular shopping district and a major auto factory. The researchers and their assistants observed cars around major intersections across the city and recorded the races of 3,840 drivers they observed. Despite the city Census population of 3% African-American, 22% of the drivers they observed were African-Americans, and the proportion of African American drivers varied from neighborhood to neighborhood across the city. In some areas of the city, 49% of the drivers were African-American. The others, 11% of the drivers were African-American.[2] Nowhere in the city did the African-American representation among actual drivers on the roadway match that of the Census demographics of the city.

A study lead by Criminologist Robin Engel, from the University of Cincinnati, examined 315,705 traffic stops conducted by troopers of the Pennsylvania State Police. These stops occurred on interstate highways, U.S. highways, state routes, county roads, and village and city streets. These stops revealed that 96% of drivers stopped by the police were stopped outside of their home zip codes. Furthermore, 66% were stopped outside of their home county, and 27% were stopped outside of their home state. In other words, 96% of the individuals stopped by these troopers were not part of the Census population of where they were stopped.

Similarly, a DCG study conducted in Ann Arbor, Michigan in 2019 found that 44% of the drivers stopped by the Ann Arbor Police Department resided outside of Ann Arbor. The study also found that, contrary to allegations based on flawed Census data benchmarks, African-American drivers were not disproportionately the subject of traffic stops. Rather, African-Americans were 1.1% less likely to be stopped than expected based on traffic collision data.

Alternative Benchmark

So what should be used as a proper benchmark for these types of reports and studies? Hiring a group of researchers to go out and record the races and traffic violations of drivers across your jurisdiction is usually too time-consuming and expensive for most law enforcement agencies. A simple solution, however, is to collect race and ethnicity data on all traffic crashes in your jurisdiction and use this data as your driver benchmark. While no state currently collects race data on its state vehicle crash form, if your agency starts collecting race data in-house, your agency will eventually have a benchmark of bad drivers across the various beats of your jurisdiction.

Using traffic crash data as a traffic stop benchmark has a number of advantages. First, it identifies the drivers most likely to be stopped because crashes result from moving or equipment violations of the law. While there are some people who are blameless for their crash (such as the person waiting at a red light who is hit from behind), all crashes had at least one driver or equipment error at fault, and many had multiple drivers at fault. Second, officers investigating traffic accidents can verify the race and ethnicity of the driver when they complete their report, as opposed to a researcher trying to determine a driver’s race in a passing car. Third, as traffic crashes occur almost everywhere (even off of public roadways in parking lots and driveways) they are good samples of the bad driver or poorly maintained vehicle population throughout a district or beat. Research observers tend to focus just on certain thoroughfares. Finally, crash data come from the citizenry who report crashes to the police, so no suggestion can be made that there was bias by the police in gathering this data.[3]

Conclusion

The overwhelming majority of racial profiling studies done by academics, and biased-based policing self-examinations by police departments, have produced results that people of color, especially African-Americans, are disproportionately stopped by the police.[4] It is likely, however, that the majority of these findings are in error as most relied on methodological errors that were guaranteed to show bias even when there was none. Using Census statistics as a benchmark, that in no way resemble the driving population or the traffic violator population, is just one of these many methodological errors.

Some key take-aways to remember with regard to racial profiling studies involving traffic stops:

  • If your agency is currently using Census data as your benchmark, it is imperative that you stop immediately and find a valid benchmark like the alternative discussed here.
  • Using Census data is unfair your officers as it almost always suggests disproportionate stops of minority group members, even when no officer bias occurred.
  • Failure to follow vetted and accepted practices in these examinations is unfair to the honest, hard-working law enforcement officers who might be erroneously accused of racial profiling, and unfair to the citizens of the community who might lose faith in their police based on findings from faulty research. 
  • If some outside individual or organization proposes to analyze your officers’ stops using Census data as their benchmark, oppose it vehemently, using the studies cited here to support your argument.
  • If your state collects statewide data, as does Illinois, Missouri, and Texas, lobby your state lawmakers to stop using Census data as the benchmark comparison and begin to collect valid benchmark comparison data by modifying the state vehicle crash form to include race and ethnicity information. 
  • If your agency or local government officials are contemplating a traffic stop study, begin collecting traffic accident demographic data as soon as possible.

Dolan Consulting Group LLC now offers training and services that addresses these many errors and offers recommendations on how to correct them. DCG’s Traffic Stop Data Analysis Services assist law enforcement agencies in the creation of data collection efforts and reporting in a fair, accurate and impartial manner. 

References

[1] Weitzer, R., & Tuch, S. A. (2005). Racially-biased policing: determinants of citizen perceptions. Social Forces, 83(3), 1009-1030.

[2] Weitzer, R., & Tuch, S. A. (2005). Racially-biased policing: determinants of citizen perceptions. Social Forces, 83(3), 1009-1030.

[3] Withrow, B. L., & Williams, H. (2015). Proposing a benchmark based on vehicle collision data in racial profiling research. Criminal Justice Review, 40(4), 449-469.

[4] Withrow, B. L. (2006). Racial Profiling: From Rhetoric to Reason. Upper Saddle River, NJ: Pearson / Prentice Hall.