Statistical Discrimination
There are always two sides to any story. The Ban the Box movement is no exception. States continue to sign it into law while reports of discrimination caused by the movement have surfaced. Ban the Box’s purpose is to remove barriers when an ex-convict applies for a job. Unfortunately, new studies show that these laws are actually encouraging a different kind of discrimination – statistical discrimination.
What is statistical discrimination? The New Palgrave Dictionary of Economics defines statistical discrimination as the use of statistical data on demographic groups instead of prejudice when assessing individuals. For instance, an employer might look at a black applicant and apply the averages of arrests for the entire black race instead of looking at that individual’s own record (or lack thereof). In that case, the applicant can be found guilty of a crime simply by fitting the statistical stereotype.
Purpose of Ban the Box
All of Us or None first introduced Ban the Box in 2004. The goal is to fight discrimination ex-convicts face when seeking employment. The argument is that asking about former convictions on job applications leads to low percentages of employment among ex-convicts. Advocates contend that requiring an ex-convict to answer this question typically leads to job disqualification.
According to a May, 2016 Harvard paper on criminal recidivism, 60 to 70 percent of ex-convicts had still not found employment after one year of release. Three years after release, more than two-thirds had been arrested again and more than 40 percent were reincarcerated. Studies point to the ex-convict’s inability to find employment as the top reason for recidivism.
Unintended Consequences
Although Ban the Box laws were introduced specifically to reduce discrimination, they have actually caused discrimination in certain cases. A study released by Amanda Y. Agan of Princeton University and Sonja B. Starr of University of Michigan Law School in June, 2016 concluded that racial statistical discrimination increased under Ban the Box laws.
According to the study, white applicants benefit the most while Blacks and Hispanics are actually being harmed. The study concludes that because the conviction question is no longer on applications, employers may inadvertently come to their own conclusion based on the race of the applicant. Because Blacks and Hispanics statistically have higher arrest rates, an applicant of this race may automatically be presumed to have a record. Since employers can’t ask – they are left to their own presumptions.
In the study, white applicants received 45% more callbacks than black applicants with similar qualifications. This compares to a 7% difference before the box was removed. The same study revealed employers that ask about prior convictions are 62% more likely to contact an applicant without a record – regardless of race.
Additional Statistics
According to Jennifer Doleac of the Brookings Institution, “Just because employers can’t see an applicant’s criminal history doesn’t mean they don’t care about it. Under ‘ban the box’, they will avoid ex-offenders by avoiding groups that are more likely to contain ex-offenders, like black and Hispanic men.”
Doleac and her colleague Benjamin Hansen held a separate study on Ban the Box policies. They concluded that employment probability for black men decreased by 4.5% and for Hispanics by 3.5%. Doleac suggests that jurisdictions repeal Ban the Box laws in order to combat statistical discrimination.
Both sides of the case can certainly agree that reintegrating ex-convicts as a valuable part of society is important. Measures need to be taken by employers to ensure fair and safe hiring practices are being followed.
Employers must still follow due-diligence when looking at potential employees. Background checks are an important part of this process. Sentinel Background Checks is a professional background check service that can guide employers through the hiring process to ensure they follow FCRA guidelines. Call (888) 725-2535 today to see how we can help!