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Racial and Ethnic Disparity in Pretrial Criminal Processing

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Abstract

This study uses data on the processing of felony defendants in large urban courts to analyze racial and ethnic disparities in pretrial processing. There are three major findings. First, racial disparity is most notable during the decision to deny bail and for defendants charged with violent crimes. Second, ethnic disparity is most notable during the decision to grant a non‐financial release and for defendants charged with drug crimes. Third, when there is disparity in the treatment of Black and Latino defendants with similar legal characteristics, Latinos always receive the less beneficial decisions. These findings are consistent with the theoretical perspective offered, which suggests that stereotypes influence criminal processing when their specific content is made salient by either the concerns relevant to a particular processing decision or the crime type of a defendant’s primary charge.
... Research on judicial decisions at pretrial is more limited and tends to emphasize stereotypes, organizational norms, and risk avoidance (Schlesinger, 2005;Sutton, 2013). The uncertainty avoidance perspective suggests judges rely on criminal history and severity of current charges that become connected to attributions of an individual's demographic characteristics (e.g., age, race, and sex; Albonetti, 1991). ...
... Attribution theory focuses on the application of negative racial and ethnic stereotypes as relevant legal factors increase their salience. This can result in racialized attributions being applied to People of Color resulting in judges finding certain individuals more blameworthy or culpable for certain crimes (e.g., drugs and violence; Schlesinger, 2005). ...
... We highlight three important features of pretrial decision making (Schlesinger, 2005). First, judges have incomplete information such that they may rely on an availability heuristic to reduce uncertainty by connecting prior criminal history and current offense with attributions related to someone's demographics. ...
Article
This paper provides the results of a thought experiment to see what would have happened if a jurisdiction made release decisions solely based on risk assessment predictions of new arrests. Random forest imputation is used with data from all admissions to a large county jail system (n = 28,188) to forecast new arrests for individuals detained by the court. After imputing outcome rates for the detained, we rank order everyone by their predicted probability of future arrest from lowest to highest probability and compare release and new arrest rates between the predicted outcomes and observed release decisions. The results show the risk-based release approach has the potential to reduce the detained population by 7% and reduce new arrests by 13% compared to current practices.
... For example, Black individuals are more likely to be held pretrial than similarly situated White persons (Demuth & Steffensmeier, 2004). In addition, Black individuals are less likely to be released on recognizance than White individuals (Freiburger & Hilinski, 2010) and more likely to be denied bail, and when bail is set, Black individuals are significantly less able to afford bail (Demuth, 2003;Schlesinger, 2005). Most research on pretrial detention suggests that women are less likely to be held in jail awaiting trial (Demuth & Steffensmeier, 2004). ...
... Prior research has shown pretrial detention and its consequences disproportionately impact Black individuals, men, and economically disadvantaged persons (Demuth, 2003;Demuth & Steffensmeier, 2004;Schlesinger, 2005). Given the documented disparities in jail incarceration and pretrial processing, we focus on understanding how race, gender, and living in a high-poverty neighborhood intersect to shape an individual's length of stay. ...
... Our analysis focuses only on individuals booked into jail via pretrial admission. The study thus centers on the pretrial population that has been highlighted as the source of racial disparities, particularly around the bail and release processes (Ball & Growette Bostaph, 2009;Demuth & Steffensmeier, 2004;Freiburger & Hilinski, 2010;Schlesinger, 2005). Individuals who were admitted to jail for a probation or parole violation, an outstanding warrant from another agency, or a hold for another agency (i.e., U.S. Immigration and Customs Enforcement) were omitted from this analysis because they typically will not have bail set and are subject to different legal processes than the traditional pretrial population (e.g., Kentucky Supreme Court Order 2017-2019, 2017; Missouri Rules of Criminal Procedure, 1979;U.S. v. Salerno, 1987). ...
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Research Summary The average length of jail stays is increasing despite national efforts to reduce these populations. The current study examines variations in lengths of stay, differentiating between short and long pretrial stays. Using data from two large jails in metropolitan jurisdictions, we take an intersectional perspective and model potential differences among race, gender, and residing in a high‐poverty area. In both locations, we find that Black men are the most likely to have long lengths of stay, but that length of stay varies depending on the intersection of gender, race, and neighborhood poverty. Policy Implications The human costs of pretrial detention are paid unequally by different groups of people. Given the downstream costs of pretrial detention, this work suggests that focusing policy efforts on the barriers to release among people of color, particularly Black men, would be fruitful. There is evidence that bail reform can reduce some barriers to release without increases in crime. Further, attending to obstacles to case processing could lead to pretrial system reform. This work also highlights another area of the criminal legal system where Black males, compared to their White counterparts, are disparately affected and denotes the continuing need for intersectional perspectives on reform.
... Racial and socioeconomic disparities in bail practices mean the health risks of pre-trial detention disproportionately affect low-income, nonwhite communities. Research has revealed that Black individuals arrested for violent crimes are 33 percent more likely to be denied bail than comparable white defendants (Schlesinger, 2005). Among those given bail, bond amounts differ by race, such that Black, Asian, and Hispanic defendants face bond amounts averaging $15,352, $34,258, and $13,529 higher than white defendants, respectively (McDowell, 2019). ...
... Most concerningly, the 1984 Act left assessment of "danger" and bail assignment to judges without provisions to prevent bias (Bail Reform Act of 1984, 1984. This leeway 4 United States v. Salerno, (481 U.S. 739 1987) effectively allowed courts to punish accused individuals regardless of guilt, and judge evaluations of "dangerousness" were often biased, as racial bias alters impressions of flight risk and potential danger (Arnold et al., 2018;Riley, 2020;Schlesinger, 2005). The 1984 Act was unsuccessfully challenged in the 1987 United States v. Salerno (Carlucci, 2020). ...
... Актуарные методы, использующие технологию искусственного интеллекта, обещают стать эффективным способом снижения предвзятости при освобождении под поручительство и вынесении приговора. Однако искусственный интеллект хорош лишь настолько, насколько хороши данные, на которых его обучали; но в течение многих лет мы систематически наблюдаем расовую предвзятость при освобождении под поручительство (Demuth & Steffensmeier, 2004b;Schlesinger, 2005;Turner & Johnson, 2005) и вынесении приговора (Demuth & Steffensmeier, 2004a;Spohn & Holleran, 2000;Western, 2006). ...
Article
Objective: to analyze the positions of judges on risk assessment tools using artificial intelligence. Methods: dialectical approach to cognition of social phenomena, allowing to analyze them in historical development and functioning in the context of the totality of objective and subjective factors, which predetermined the following research methods: formal-logical and sociological. Results: Artificial intelligence (AI) uses computer programming to make predictions (e.g., bail decisions) and has the potential to benefit the justice system (e.g., save time and reduce bias). This secondary data analysis assessed 381 judges’ responses to the question, “Do you feel that artificial intelligence (using computer programs and algorithms) holds promise to remove bias from bail and sentencing decisions?” Scientific novelty: The authors created apriori themes based on the literature, which included judges’ algorithm aversion and appreciation, locus of control, procedural justice, and legitimacy. Results suggest that judges experience algorithm aversion, have significant concerns about bias being exacerbated by AI, and worry about being replaced by computers. Judges believe that AI has the potential to inform their decisions about bail and sentencing; however, it must be empirically tested and follow guidelines. Using the data gathered about judges’ sentiments toward AI, the authors discuss the integration of AI into the legal system and future research. Practical significance: the main provisions and conclusions of the article can be used in scientific, pedagogical and law enforcement activities when considering the issues related to the legal risks of using artificial intelligence.
Article
Research summary This study provides a rigorous assessment of the public safety benefits of pretrial detention by estimating the criminogenic and punitive effects of spending at least 1 week in pretrial detention across three jail systems in two states. We use a doubly robust difference‐in‐differences design to show that pretrial detention increases the odds for someone to miss a court appearance or be arrested by roughly 50% and increases the odds of convictions by 36%. This evidence was support by a series of supplemental analyses demonstrating that spending more than 1 day and spending more than 3 days in pretrial detention increased the odds of negative pretrial outcomes compared to someone who was booked and released from jail. The findings of this study provide evidence that pretrial detention can be counterproductive to public safety in that it leads to increased likelihood that individuals will miss court and be arrested for new crimes. Policy implications Jails are a unique criminal justice contact point because they hold individuals at different stages of case processing, including individuals awaiting trial, and those serving shorter sentences or waiting to be transferred to prison. Pretrial release is arguably one of the most consequential decisions in case processing for an individual. Combining our findings with the punitive and collateral effects of time spent in pretrial detention signals a need for policies to identify effective methods of release that maximize liberty, safety, and equity and minimize the criminogenic effects of pretrial detention. Jails are inhabited with pretrial detainees, detention makes outcomes worse for these detainees, and detention does not deliver on public safety as intended. We argue that a more limited and targeted use of pretrial detention is needed and more research attention on alternatives to pretrial detention.
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