Assessing Sentencing Disparities among American Indians within the Eighth, Ninth, and Tenth Federal Circuit Courts

ABSTRACT

In a fair and equitable criminal justice system, one’s race should not influence their sentencing outcomes. Research studies conducted in the United States often report evidence that ethnic minorities are at an increased risk for receiving more punitive punishments at the time of their sentencing. The existing scholarship, however, has largely focused on assessing differences between Black and Hispanic defendants in relation to White defendants. There has been far less academic exploration of potential sentencing disparities among other less populated ethnic groups, including American Indians. To address this gap in knowledge, we use data collected from the United States Sentencing Commission to test whether American Indians receive different sentencing outcomes when compared to other racial groups. Our study findings indicate that American Indian defendants are more likely to be sentenced to prison than White, Black, and Hispanic defendants, but among those incarcerated, American Indians received similar sentence lengths to Whites.

KEYWORDS:

• federal courts
• Native Americans

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. These three circuits include the following jurisdictions: Alaska, Arizona, Arkansas, California, Colorado, Guam, Hawaii, Idaho, Iowa, Kansas, Minnesota, Missouri, Montana, Nebraska, New Mexico, North Dakota, Northern Mariana Island, Oklahoma, Oregon, South Dakota, Utah, Washington, and Wyoming.

2. We excluded immigration offenses because Native American and Alaska Natives are United States citizens and are not subject to prosecution for this type of crime.

3. One of the assumptions of OLS regression is that the dependent variable is normally distributed. It is often recommended that variables with a skewness value greater than the absolute value of 1 be transformed before use in OLS regression. The skewness value for sentence length was 5.81, which suggests that the variable should be transformed. After the log transformation, the skewness value was reduced to −.85, which indicates that OLS regression modeling is an appropriate strategy for analyzing this outcome.

4. We excluded other races, including Asian and Pacific Islander, due to so few cases falling within each category (i.e., < 2%).

5. This measure was also naturally logged to account for its skewed distribution. The skewness value went from 10.64 to .47 following the log transformation.

6. As a supplemental analysis, we conducted a negative binomial regression model with incarceration length as the dependent measure and the results were substantively similar to those produced via OLS regression. The Native American variable was small in magnitude and not statically significant (β = .006, p = .745). We thank one of the anonymous reviewers for recommending this analysis as a robustness check.

7. Although not statistically significant at the .01 level, the magnitude of the effect of Black on incarceration is still concerning; Blacks were 21% more likely to be incarcerated than Whites (see Table 3).