The Adjudicatory Capacity to Make Decisions

Scholar suggests that increasing the number of support staff would improve the accuracy of administrative adjudication.

“In essence, we’re doing death penalty cases in a traffic court setting,” stated judge Dana Leigh Marks as she described her work as an immigration judge in 2017. Today, 540 immigration judges rule on life-or-death decisions in more than 1.5 million cases every year, raising questions about how accurate their judgments can be.

In a forthcoming article, Nicholas Bednar argues that increasing the number of law clerks assigned to judges in adjudicatory agencies would make their rulings more accurate by increasing “adjudicatory capacity”—which describes the resources needed for adjudicators to perform their job in an accurate and efficient way.

Although adjudicatory agencies have the authority to resolve disputes, they lack the staff to deal with their high workload. As a result, civil servants may rely on coping mechanisms, such as procedural shortcuts that harm the quality of the public services they provide. Judges may also use heuristics, or rules of thumb, that often lead to the use of racial, ethnic, or religious stereotypes.

But according to Bednar, law clerks play a critical role in achieving more accurate results and expanding adjudicatory capacity. They can take on responsibilities that have no technological substitute, such as reviewing administrative records, conducting research, and drafting orders.

To explore how adjudicatory capacity affects the quality of administrative rulings, Bednar analyzes one such agency as a case study: the Executive Office of Immigration Review (EOIR). The EOIR is an agency within the U.S. Department of Justice that administers the immigration court system. In turn, the immigration courts review cases the Department of Homeland Security brings against individuals charged with violating immigration law. During these hearings, an immigration judge determines whether the United States should remove or grant protection, such as asylum, to the respondent.

Bednar chose the EOIR as a case study for two reasons. First, he argues it is easier to estimate the accuracy of EOIR decisions because respondents must reach a high bar to avoid being removed. Because of this high bar, a researcher can have a high confidence in the accuracy of rulings granting protection to respondents. Second, the EOIR illustrates how crucial decisions rest in the hands of federal bureaucrats in the adjudicatory agencies. Their rulings have dramatic consequences in respondents’ lives, from their immigration status to their eligibility for Social Security benefits.

When Bednar examined 1.5 million EOIR removal orders between 2004 and 2022, he found that judges with the fewest law clerks were more likely to remove respondents and less likely to grant them asylum. Bednar divided judges into three groups by the number of law clerks assisting them, where low-capacity describes judges with the fewest law clerks.

His empirical analysis showed that respondents assigned to low-capacity judges were 12 percent more likely to be removed than respondents assigned to average-capacity judges. Similarly, respondents assigned to low-capacity judges are 4 percent less likely to be granted asylum compared to average-capacity judges.

Although the differences between low-capacity and average-capacity judges are clear, the number of law clerks appeared to matter less between average-capacity and high-capacity judges. For example, respondents assigned to high-capacity judges were 1 percent less likely to be removed than respondents assigned to average-capacity judges. And respondents assigned to high-capacity judges were actually 3 percent less likely to be granted asylum than respondents assigned to average-capacity judges.

A more sophisticated statistical model developed by Bednar, however, indicated that there is a stronger connection between the number of clerks and the likelihood of removal or a grant of asylum. Rather than relying only on the number of law clerks, this sophisticated model accounted for confounding variables such as geographic differences and the number of cases assigned to each judge.

In addition to concluding that maintaining an average-capacity of law clerks improves the accuracy of immigration judges, Bednar showed how adjudicatory capacity makes judges rely less on coping mechanisms such as shortening the length of hearings.

To test for this effect, Bednar analyzes how the Trump Administration’s 2018 performance metrics impacted the length of the hearings. The new metrics required an immigration judge to complete a minimum of 700 cases per year and shorten timeframes for certain hearings in order to attain a satisfactory rating.

The data showed that the new policy affected courts differently depending on their adjudicatory capacity: high-capacity judges shortened hearings by two minutes on average, whereas low-capacity judges shortened hearings by more than ten minutes. That meant immigration judges with fewer law clerks were more likely to implement coping mechanisms that could affect the quality of their work and accuracy of their rulings.

Amid growing concerns about the fairness in agency adjudications, Bednar’s study illustrates how higher adjudicatory capacity promotes more accurate outcomes. Investing in adjudicatory capacity might allow immigration judges to devote greater attention to life-or-death cases deserve, according to Bednar.