The Interrelationship between Area Deprivation and Ethnic Disparities in Sentencing: An Analysis of Administrative Data from the Crown Court
In the study of sentencing disparities, class related hypotheses have received considerably less attention than explanations based on offenders’ ethnicity. This is unfortunate since the two mechanisms are likely interrelated, at the very least as a result of their overlap in the population, with ethnic minorities being generally more deprived than the White majority. In this registered report we propose exploring the mediating and moderating effects between offenders’ area deprivation and their ethnic background using a novel administrative dataset capturing all offences processed through the England and Wales Crown Court. Specifically, we seek to test two key hypotheses: i) the reported ethnic disparities in sentencing are mediated and explained away by area deprivation; and ii) ethnic disparities are moderated by area deprivation, with ethnic disparities being narrower in the more deprived areas. Results from this empirical analysis will shed new light on the underlying causes of sentencing disparities, but crucially – if deprivation is shown to play a major role in the generation of ethnic disparities – they will also help inform the adequate policy responses to redress this problem.
Ethnic Disparities in Sentencing: Warranted or Unwarranted?
Large research efforts have been directed at the exploration of ethnic disparities in the criminal justice system, documenting harsher treatment of minority ethnic defendants, across offence types, criminal justice decisions, and jurisdictions. However, most studies on the topic have relied on observational data, which can only approximate ‘like with like’ comparisons. As a result, researchers, practitioners and policy-makers have often been wary of interpreting such disparities as evidence of discrimination. We use causal diagrams to lay out explicitly the different ways estimates of ethnic discrimination derived from observational data could be biased. Beyond the commonly acknowledged problem of unobserved case characteristics, we also discuss other less well-known, yet likely more consequential problems: measurement error in the form of racially-determined case characteristics or as a result of high heterogeneity within the ‘Whites’ reference group, and selection bias from non-response and missing offender’s ethnicity data. We apply such causal framework to review findings from two recent studies showing ethnic disparities in custodial sentences imposed at the Crown Court (England and Wales), questioning whether the reported disparities should be interpreted as evidence of discrimination. We also use simulations to recreate the most comprehensive of those studies, and demonstrate how the reported ethnic disparities appear robust to a problem of unobserved case characteristics. We conclude that ethnic disparities observed in the Crown Court are likely reflecting evidence of direct discrimination in sentencing.
Does the Crown Court Discriminate Against Muslim-Named Offenders? A Novel Investigation Based on Text Mining Techniques
Most research in sentencing discrimination in the UK has relied on aggregate analyses comparing disparities by ethnic group. These studies fail to consider differences in the individual characteristics of the cases processed. To circumvent the lack of official data we scraped sentence records stored in a commercial website to create a sample of 8,437 offenders sentenced to custody in the Crown Court from 2007 to 2017. Using the names of the offenders we have been able to classify 8% of our sample as having a traditional Muslim name. We find that Muslim-named offenders received sentences 9.3% longer than the rest of the sample. However, this difference disappeared once we accounted for the type of offence and other key case characteristics.