Revisiting the Normal Crime and Liberation Hypotheses

Abstract

The established sentencing scholarship focusing on race/ethnicity and sentencing disparity indicates that the effect of race/ethnicity on sentencing severity varies across offense types. However, it is not clear whether this argument holds true when race/ethnicity is replaced with offender citizenship status as the primary variable of interest. In light of the research gap, this study extends beyond the existing literature exclusively on race/ethnicity by investigating the nexus between citizenship status, offense types, and sentencing outcomes through the normal crime hypothesis and the liberation hypothesis. Using the Monitoring of Federal Criminal Sentences data that include information on all offenders sentenced in 17 federal district courts for fiscal years 2006-2008, the present study assesses the independent and interactive effects of citizenship status and offense types on the judicial sentence length decision. Findings reveal that although models fail to support the normal crime hypothesis, there is robust support for the liberation hypothesis.It has been more than four decades since the normal crime and liberation hypotheses drew the attention of scholars in criminal courts and sentencing. According to the normal crime hypothesis, the regular characteristics of offenses and offenders lead courtroom actors to develop norms of processing a case effectively; as a result, cases may be handled differently, depending on whether a particular offense is considered typical of the specific group to which the offender belongs (see Hawkins, 1987;Sudnow, 1965). The liberation hypothesis suggests that courtroom decision makers are liberated from legal restrictions and have greater discretion in deciding a case when there is a high degree of ambiguity about a case or when the seriousness of an offense is low

Disparate incarceration rates of foreign citizens in Europe compared to Anglo‐Saxon countries

“…(2011) found that both legal and illegal noncitizens were more likely to receive sentences of incarceration than U.S. citizens, although illegal aliens were given significantly shorter sentences than citizens. Wu and DeLone (2012) found similar results when examining the treatment of noncitizen offenders during sentencing. Both studies suggested that this may be because illegal aliens were likely to be deported after completing their sentences, providing judges with a cost‐based incentive to impose a shorter term of incarceration.…”

The Noncitizen Penalty in U.S. Federal Courts: Differences in Punishment by Region of Citizenship

“…However, contrary to expectations, our results indicate that undocumented legal status is negatively associated with sentence length. We interpret this latter finding as reflective of the high likelihood that undocumented noncitizens will be deported following a conviction in federal court, which likely renders lengthy sentences in prison less of a priority (see Wu and DeLone 2012).…”

“…A small number of studies have found that noncitizens are penalized net of the disadvantage associated with their race/ethnicity (Light 2014; Wu and D’Angelo 2014). Yet the majority of research on citizenship and sentencing has not examined variation in the noncitizen effect by the defendant’s nation of citizenship (e.g., Light 2014; Light et al 2014; Wu and D’Angelo 2014; Wu and DeLone 2012). The few studies that have done so limit analyses to drug offenses (Iles and Adegun 2018; Logue 2009), examine only courts outside of the continental United States (Iles 2009), compare within one ethnicity (Logue 2009), or do not provide a comparison to U.S. citizens (Iles and Adegun 2018).…”

“… 5. Sentence length and incarceration are fundamentally linked through a selection process, such that sentence length is only observed for defendants who were sentenced to incarceration. Although some research uses the Heckman correction procedure to address this potential source of bias (Bushway, Johnson, and Slocum 2007), the Heckman correction can be more problematic than modeling the processes separately due to issues of collinearity (Light, Massoglia, and King 2014; Wu and DeLone 2012). In addition, federal data contain a high proportion of individuals sentenced to incarceration (88.11 percent in our data set), so selection bias is less problematic than in other contexts (see Light 2014 for discussion).…”