Disparities at Points of Prosecutorial Discretion

Twentieth Judicial District Attorney — Disparities at Points of Prosecutorial Discretion

The fair and just treatment of all communities at each stage of the criminal justice process is of significant importance. Central to this discourse is a recognition of the discretionary power that prosecutors wield in shaping the outcomes of criminal cases. This includes, among other things, the decision to prosecute or decline to file charges, adjust the severity of charges, dispose of cases through dismissal, deferral, or plea negotiations, and make sentencing recommendations. It is valuable to examine such points of discretion to understand whether there are differences in outcomes across individuals of different races/ethnicities.

Colorado's 20th District Attorney's (DA) Office data dashboard, released in September 2022, provides a diagnostic tool to identify what is happening. However, if we see differences, for example, between White and Black individuals, what does that tell us?

Digging Deeper. What do Differences Mean?

To support actionability, it is important to dig deeper, distinguishing between two important concepts– disproportionality and disparity–and considering system drivers of potential differences.

Disproportionality. The DA's Office receives cases after law enforcement agencies make an arrest. Disproportionality exists when more people of a certain race/ethnicity are arrested than we would expect given the population. Race and ethnicity are captured separately in the census and the DA's case management system. The DA's case management system is limited in that individuals cannot be identified as mutiracial, and it is rare that both the race and ethnicity for an individual are recorded. To help address this limitation and support an equitable approach, which aims to review and present data in ways that align with how individuals identify (Pew Research Center, Schusterman Family Philanthropies), we have combined the race and ethnicity fields.

When looking at cases referred to the 20th Judicial District Attorney's Office between March 2020 and June 2022, we see the following with regard to disproportionality:

With regard to Hispanic individuals:

• If only considering ethnicity, 14.6% of individuals in Boulder county identify as Hispanic. This compares with 20.6% of individuals referred to the DA's Office.
• When considering race and ethnicity together, data suggest that 8.5% of individuals in Boulder county identify primarily as Hispanic (whereas 5.5% identify as Hispanic + multiracial and 0.5% identify as Hispanic + Black, Native American, or Asian; therefore, are represented in those categories). This compares with 20.5% of individuals referred to the DA's Office.

With regard to Black individuals:

• When considering race and ethnicity together, 1% of individuals in Boulder county identify as Black. This compares with 5.3% of individuals referred to the DA's Office.

Any decisions made by the DA's Office are "downstream" from the first decision in criminal case processing: who is arrested. Where there are racial disproportionalities in the raw number of people arrested, it follows that those disproportionate numbers flow throughout the prosecution process.

Disproportionality may not necessarily be explained by differences in criminal behavior. It can also be due to the behavior of criminal justice actors, like law enforcement practices and resource allocation that result in more people of color being stopped and arrested, or crime trends and enforcement responses in certain neighborhoods.

Disparity. Disparity exists when people who should be treated the same are treated differently. As noted, the current data dashboard presents raw differences. Any differences we see could be the result of differences in cases (e.g., severity of charges), defendants (e.g., criminal history), and/or prosecutorial practices. To support understanding and actionability, it is important to compare similarly situated defendants and similar types of cases. This will help us understand the extent of, and potential reasons for, any disparities.

Systemic Drivers of Disparities. Appropriately, prosecutors evaluate each case on its own merits. While decisions and criteria used to make decisions may seem unrelated to race on a case-by-case basis, they may be influenced by systemic drivers that are correlated with a defendant's race/ethnicity (Figure 1, below). For example, Black and Hispanic defendants, due to historical inequities, may have unequal access to resources such as educational opportunities, formal medical diagnoses, and steady employment. These circumstances could influence factors that prosecutors consider in their decision-making, such as previous criminal history, ability to pay restitution, or engagement in drug treatment.

Figure 1. Examples of Systemic Drivers of Racial/Ethnic Disparities

Likewise, prosecutors may have different interpretations of defendants' life circumstances and experiences. Defendants may have diverse expressions of concepts such as remorse, respect, or compliance, which may or may not align with prosecutors' expectations. Likewise, prosecutors may differ in their interpretation of a defendant's life circumstances, attitudes, or behaviors. Importantly, our methodology cannot be used to support or refute possible implicit or explicit bias.

We hope this analysis will prompt a conversation about what systemic drivers of racial/ethnic disparities exist and how a DA's Office might work to address them. In reviewing the results we encourage you to take a systemic perspective, considering the variety of potential drivers noted above.

Analysis Focus

This analysis focused on the outcomes of prosecutorial decision making in the DA's Office from March 2020 through the end of June 2022. We assessed the extent of racial and ethnic disparities across the following three decision points: (1) dispositions (dismissal, deferred judgment, and plea agreement) for felony and misdemeanor offenses; (2) charge reduction from filing to disposition for felony and misdemeanor cases; and (3) imposition of an incarceration sentence (Figure 2, below). We prioritized the areas where the DA's Office has the greatest direct influence and where we had accurate and reliable data.

Figure 2. Decision Points Analyzed

A more comprehensive overview of how a case moves through the system can be found here.

As noted above, for this analysis, we combined the race and ethnicity fields. Due to known challenges in accurately collecting Hispanic ethnicity, we used defendants' last name, linked with census data, to help us better identify Hispanic individuals. See Terms, Methods, and Limitations for more information.

This analysis aims to prompt discussion and raise questions, rather than provide definitive answers. To support this aim, we present results as predicted probabilities: an estimate of the likelihood of the outcome, based on the defendant's race/ethnicity, while taking into account individual and case factors. Information on statistical significance, which is heavily influenced by sample size, can be found in the technical appendix.

Key Takeaways

This study, which includes data as recent as June 2022, shows positive trends of low disparity. While disproportionality exists in terms of who is referred to the DA's Office, once cases hit our office, they are largely treated similarly. We will continue to monitor these numbers and continue to take steps as an office and as leaders in the state to improve disparities and disproportionality. The analysis highlighted four data points that we will explore:

The analysis highlighted four data points that we will explore:

• Black defendants receive deferred judgments at a lower rate and have an increased dismissal rate.
• Hispanic defendants show smaller rates of charge reductions in plea bargaining and have a higher rate of incarceration.
• These data points appear consistent with trends at other DA's Offices, which require us to look at systemic drivers of any disparities.

This data will continue to improve as more of the 22 Judicial Districts in Colorado participate in and are added to the dashboard project. For this analysis, criminal history was run only across the eight participating jurisdictions. Those eight jurisdictions do not include our neighboring counties of Weld and Broomfield. Given that areas in our community, such as Longmont, are split between two counties, we are curious to see how adding more jurisdictions might give us more accurate information on controlling for criminal history. While criminal history can exacerbate racial and ethnic disproportionality and disparities (such as certain neighborhoods being policed more heavily, research that shows Black children are often assumed to be older than they are, etc.), we must consider criminal history in resolving cases as a defendant with no history and one with six prior felonies should be and are differentiated and treated differently. Similarly, in charges like Driving Under the Influence (DUI), the law requires us to treat defendants with history differently than those without a history, such as requiring mandatory jail sentences on a second or subsequent DUI, and by classifying a fourth DUI as a felony.

Actionability

• In 2023, the DA's Office will train on systemic drivers of disproportionality and disparities and how our prosecutors should consider these when exercising their discretion.
• We are increasing adult diversion screening of cases, improving screening processes, and plan to capture diversion data better. We have seen through our juvenile diversion screening process that broader screening of cases results in more equitable outcomes in referrals for diversion.
• We hope to hire an in-house data analyst and launch a crime strategies unit. Having a data analyst and launching a crime strategies unit will allow us to better monitor trends over time and to continue digging into disparities and disproportionalities.
• We will continue our efforts to improve data collection and data entry accuracy, such as better collection of race and ethnicity data and entry of reasons for dismissal. Tracking reasons for dismissals will allow us to track trends to understand how and why prosecutors are exercising their discretion.

Disposition

This analysis considers felonies and misdemeanors filed between March 1, 2020 and June 30, 2022 for individuals identified as White, Black, or Hispanic. Our sample includes 11,301 cases that were disposed of during that time frame. The racial/ethnic breakdown of defendants in our sample was: 72.5% White (8,190), 22.2% Hispanic (2,504), and 5.4% Black (607).

Case outcomes. Of the cases in our sample, 55.8% were resolved through plea agreements, 17.0% through dismissal, 14.0% through deferred judgments, 12.4% through a global plea, and 0.8% through a trial. Systematic data on other outcomes, such as diversion, are not available.

Differences Among Defendants. There were some differences among defendants. Hispanic and Black individuals were younger than White individuals. White individuals were less likely to have a criminal history. Black individuals had higher rates of having cases involving a felony charge (vs. misdemeanor) filed. It took longer to resolve cases for Black individuals.

More on differences among defendants

• Age and gender: In general, Hispanic and Black individuals were younger than White individuals. For example, 38.0% of Hispanic individuals and 34.3% of Black individuals were under the age of 26, compared to 28.3% of White individuals. Black individuals were more likely to be male (82.4%), compared to White (73.8%) and Hispanic (74.8%) individuals.
• Criminal history: White individuals were less likely to have a criminal history. 57.3% of White individuals had no prior convictions, compared to 52.2% of Black individuals and 52.8% of Hispanic individuals. A greater proportion of Black individuals (15.0%) had prior non-violent felony convictions, compared to White (13.0%) and Hispanic (12.7%) individuals. A greater proportion of Hispanic individuals (8.9%) had prior violent felony convictions, compared to Black (6.4%) and White (6.2%) individuals.
• Charge level and charge type: Cases involving Black individuals were more likely to include a felony charge (30.0%), compared to those involving White (23.9%) and Hispanic (23.2%) individuals. In looking at charge type, cases involving Black individuals had a higher percentage of person or sex charges. Cases involving White individuals had a higher percentage of DUI charges. Cases involving Hispanic individuals had a higher percentage of traffic charges.
• Case Length: It took longer to resolve cases for Black individuals, with a mean of 5.7 months (standard deviation [SD]: 5.0), compared to 5.1 months for Hispanic individuals (SD: 4.7) and 5.0 months for White individuals (SD: 4.5).

Dismissal

A case is dismissed when the criminal charges are terminated, either by the court or by the prosecutor. There can be several reasons why a case is dismissed, including: a lack of evidence or unavailability of a witness. Cases may also be noted as dismissed if they are referred to, or successfully complete, a diversion program.

Total Dismissed: Our sample included 1,917 cases that were dismissed. Dismissals accounted for 17.0% of case dispositions in the sample. Overall, 20.3% (123) of cases involving Black individuals, 16.8% (1,376) of cases involving White individuals, and 16.7% (418) of cases involving Hispanic individuals were dismissed. These represent raw rates: any differences we see could be due to differences in individual or case characteristics.

Deferred Judgment

A deferred judgment is an alternative to traditional prosecution that attempts to address individuals' needs and to offer alternatives such as useful public service, probation, payment of restitution, or counseling or treatment related to their case. The defendant enters a temporary guilty plea, and, if they comply with the terms, their guilty plea is withdrawn and the case is dismissed. If an individual does not comply with the terms of their deferred judgment, the temporary guilty plea becomes permanent, and they are then sentenced.

Total Deferred. Our sample included 1,586 cases that were deferred. Deferrals accounted for 14.0% of case dispositions in the sample. Overall, 14.2% (1,162) of cases involving White individuals, 14.1% (353) of cases involving Hispanic individuals, and 11.7% (71) of cases involving Black individuals were deferred. These represent raw rates: any differences we see could be due to differences in individual or case characteristics.

Plead Guilty

An individual pleads guilty when they admit a factual basis for the plea and acknowledge guilt for a charge, sometimes in exchange for a more lenient sentence.

Total Plead Guilty: Our sample included 6,310 cases that resulted in a guilty plea. Guilty pleas for 55.8% of case dispositions in the sample. Overall, 56.4% (1,411) of cases involving Hispanic individuals, 56.0% (4,584) of cases involving White individuals, and 51.9% (315) of cases involving Black individuals resulted in a guilty plea. These represent raw rates: any differences we see could be due to differences in individual or case characteristics.

Charge Reduction

After a prosecutor files a case, the top charge in the case may change over time as some charges are dismissed or amended between filing and disposition. In this section, we considered reductions in the severity of charges from initial filing to disposition for cases that plead or were found guilty.

Total Charge Reduction: Of the 6,310 cases that resulted in a guilty plea, 34.3% had no charge reduction, 23.5% had a within charge level reduction (either from a more severe felony to a less severe felony, or from a more severe misdemeanor to a less severe misdemeanor), and 42.2% were reduced across charge levels (from a misdemeanor to a petty offense/infraction or from a felony to misdemeanor or petty offense/infraction). Overall, the breakdown across racial/ethnic groups was:

• No reduction: 34.9% White (1,599), 34.2% Hispanic (482), and 27.3% Black (86).
• Within charge level reduction: 27.1% Hispanic (383), 24.1% Black (76), and 22.3% White (1,022).
• Across charge level reduction: 48.6% Black (153), 42.8% White (1,963), and 38.7% Hispanic (546).

These represent raw rates: any differences we see could be due to differences in individual or case characteristics.

Sentenced to Incarceration

After an individual is found guilty of a crime, a judge imposes a sentence which may include fees, fines, community service, probation, jail, community corrections, or prison. Prosecutors and defense attorneys can negotiate plea bargains or make sentencing recommendations to the judge, who decides on the ultimate sentence. Incarceration includes any jail sentence (with or without probation), community corrections, or prison.

Total Incarceration: Of the 6,310 cases that resulted in a guilty plea, 18.8% had an incarcerative sentence. Overall, 21.9% (69) of cases involving Black individuals, 21.6% (305) of cases involving Hispanic individuals, and 17.8% (815) of cases involving White individuals resulted in an incarcerative sentence. These represent raw rates: any differences we see could be due to differences in individual or case characteristics.

Conclusion

The fair and just treatment of all individuals at each stage of the criminal justice process is of significant importance. We hope this analysis will prompt a conversation about what systemic drivers of racial/ethnic disparities exist and how a DA's Office might work to address them. We welcome your reflections on the findings and potential next steps.

A project of the Colorado Evaluation and Action Lab, the Loyola Chicago Center for Criminal Justice, and the Prosecutorial Performance Indicators.

Terms, Methods, Limitations

Terms

Case: A collection of charges against a defendant arising out of a single incident. In this analysis, cases are classified by their most serious charge.

Controlling: Taking other factors into account when conducting an analysis. For example, "after controlling for age, gender, criminal history" means that we are taking potential differences in these factors into account when examining the differences between White, Black, and Hispanic defendants.

Predicted Probability: An estimate of the likelihood of the outcome, based on the defendant's race/ethnicity, while taking into account the control variables.

Standard Deviation: A measure of how dispersed the data are in relation to the mean. Low standard deviation means data are clustered around the mean, and high standard deviation indicates data are more spread out.

Methods

Data Source

All data was drawn from the Action case management system, stored and shared by the Colorado District Attorneys' Council (CDAC).

Variable Construction

Race/Ethnicity: As outlined in the data dashboard, race and ethnicity are determined by law enforcement. For this analysis, we combined the race and ethnicity fields. If an individual was identified as White and Hispanic, we categorized them as Hispanic. If the individual's race was identified as Black, we categorized them as Black, regardless of their ethnicity. If the individual's race was identified as Native American, we categorized them as Native American, regardless of their ethnicity. Because we believe that Hispanic individuals were systematically miscategorized as White in the dataset, we used the defendant's last name to help identify their ethnicity. Based on procedures employed by the Colorado Department of Public Safety in their CLEAR Act reporting, we recategorized any individual as Hispanic who met the following criteria: 1) their race was identified as "White," "other," or their race was missing and 2) the 2010 census file (surnames occurring 100 or more times) identified their surname as having 85% or more individuals with that surname as "Hispanic or Latino". This procedure resulted in the categorization of an additional 1,907 (10.3%) cases with Hispanic defendants.

Age: We used the following age categories: under 18, 18-25, 26-35, 36-45, and over 45 years old.

Gender: Law enforcement defines gender in the following categories: male, female, other. Due to the small number of individuals identified as "other," we limited our analysis to individuals identified as male or female.

Criminal History: As outlined in the data dashboard, we calculated criminal history based on convictions (since 2007) within the 8 District Attorneys' Offices participating in the Colorado Prosecutorial Dashboards Project (the 1st, 2nd, 5th, 6th, 7th, 8th, 18th, and 20th). We developed four categories: a) no criminal history, b) prior misdemeanor convictions, c) prior non-violent felony convictions, and d) at least one prior violent felony conviction. The definition of violent was aligned with the definition used in the dashboard.

Charge Level: Charge represents the most serious filed charge, categorized as a felony or a misdemeanor.

Charge Class: Charge class represents the most serious filed charge, which we categorized as follows: a) felony 1-4 or drug felony 1-3, b) felony 5-6 or drug felony 4, c) misdemeanor 1-2 or drug misdemeanor 1-2, d) misdemeanor 3, or e) traffic misdemeanor 1-2.

Charge Type: As defined in the data dashboard, we classified cases by their top charge into the following categories: person or sex, property, drug, driving under the influence (DUI), traffic, weapons, or other.

Case Length: We calculated the case length as the number of months to case resolution, using the date the case was filed and the date the case was disposed of. We treated values less than zero or more than five years as missing.

Disposition Quarter: To account for time trends, we constructed a categorical variable representing the calendar year quarter the case was disposed.

Case Disposition (Dismissal): We identified all cases that had a disposition of "dismissed" for the most serious filed charge. We did not include plea dismissals (a defendant's case/cases dismissed in exchange for pleading guilty to another case/cases).

Case Disposition (Deferred Judgment): We identified all cases for which a defendant received a deferred judgment to the most serious filed charge.

Case Disposition (Plead Guilty): We identified all cases in which the defendant plead guilty to the most serious filed charge.

Charge Reduction: We developed three ordered categories of charge reduction from filing to disposition: a) no reduction b) within class reduction (for example, a felony 1 to a felony 3 or a misdemeanor 2 to a misdemeanor 4), and c) a charge level reduction (a reduction from a misdemeanor to a petty offense/infraction or a reduction from a felony to a misdemeanor or petty offense/infraction).

Referral Reduced at Charging: Referral charge reduction represents whether the felony referred was reduced to a misdemeanor at point of filing.

Incarceration: As defined in the data dashboard, a sentence to incarceration included any of the following sentences: state prison, youth corrections, community corrections, jail, or any sentence of jail and probation, as well as inmate/outmate programs, work release, in-home detention, and weekenders.

Census Race and Ethnicity

The District's Population was generated from information publicly available through the United States Census Bureau. The 2020 U.S. Census collected race and ethnicity as two questions. In combining the race and ethnicity questions, we used the following logic: If an individual identified as White and Hispanic, we categorized them as Hispanic. If an individual identified as Black, we categorized them as Black, regardless of their ethnicity. If an individual identified as Native American ("American Indian or Alaska Native" or "Native Hawaiian and Other Pacific Islander") we categorized them as Native American, regardless of their ethnicity. Because data suggest that individuals who identify as Hispanic, often report their race as "some other race," (Pew Research Center), we categorized individuals who identified as "Some Other Race" and Hispanic as Hispanic. We categorized individuals that selected two or more races, regardless of their ethnicity, as "Multiracial or Another Race."

Analytic Sample

This analysis focused on cases filed and disposed of by the DA's Office from March 2020 through the end of June 2022. We focused on that timeframe based on feedback from the Office that this was the period for which the most reliable data on race and ethnicity were available. All analyses were focused on the most serious charge.

We focused on defendants identified as Black, White, and Hispanic. Due to small sample size, we excluded individuals identified as Asian (208, 1.1%) or Native American (105, 0.6%). We excluded individuals whose race/ethnicity was unknown (560, 3.0%). To avoid grouping individuals with diverse identities, we also excluded individuals identified as another race/ethnicity (452, 2.4%).

To conduct a complete case analysis, we limited our analyses to individuals with complete data on all of the variables of interest. We excluded individuals with missing data on gender, age, criminal history, any felony referrals declined at filing, open cases, and cases not yet disposed of on July 1, 2022. We limited our analyses to cases that had either a misdemeanor or felony charge at point of filing. We excluded fugitive cases. Lastly we only kept cases with complete data on case length and disposition quarter. This excluded a total of 5,869 cases (34.2%).

Analysis Procedures

We conducted all analyses using Stata 17.0 (Statacorps, 2021). We began by conducting descriptive and bivariate analyses, examining the association between race/ethnicity and all outcomes and covariates.

We used logistic regression to examine the association between the three disposition outcomes (dismissed, deferred judgment, and plead guilty) and incarceration and race/ethnicity. We included gender, age, criminal history, case length, disposition quarter, charge type, and charge class as covariates.

We used a generalized ordinal logistic regression model to examine the association between charge reduction and race/ethnicity. We selected a generalized original logistic model because the likelihood-ratio test suggested that the proportional odds assumption was violated in the ordinal model. We included gender, age, criminal history, case length, disposition quarter, charge class, charge type, and whether the referral charge was reduced at filing as covariates.

For all models, we conducted stratified analysis, looking for potential differential impacts by charge class, charge type, the top five most frequent charges, gender, and age. When presenting results for stratified analysis, we considered categories that had the highest proportion of cases within that outcome (e.g., types of cases most frequently resolved by plea agreement), while aiming to avoid small cell sizes (less than 50).

To support interpretation, we used the margins command to calculate mean predicted probabilities using the sample values of the other predictor variables. Given sample sizes and equity considerations, we have chosen to report p-value in the technical appendix.

Limitations

This analysis has a number of limitations:

• We do not have any information on why cases were dismissed or received a deferred judgment. Likewise, it is not possible to tease out whether cases were dismissed because they were referred to or successfully completed a diversion program.
• We are using a proxy measure of criminal history. As noted on the dashboard, we do not have information on convictions outside the 8 pilot DA Offices participating in the Colorado Prosecutorial Dashboard Project or cases from outside the state of Colorado. Likewise, we only have data since 2007. For these reasons, criminal history may be underestimated. However, when benchmarked against data from the Bureau of Justice Statistics, criminal history was found to be of similar magnitude.
• Race and ethnicity is reported to the DA's Office by law enforcement agencies. Law enforcement currently captures this data through various mechanisms: (1) by linking to prior criminal history records, (2) by scanning a Colorado ID or driver's license, (3) through fingerprint technology, or (4) based on the officer's "perceived demographic information of the person contacted" (as required by HB21-1250). Officer assumptions have the potential to lead to inaccurate or inconsistent data. We have attempted to correct potential under-identification of Hispanic individuals using census data. While we were able to test this correction using a small sample of individuals who self-reported race to Jefferson County Pretrial Services, we have no way to assess to what extent this correction is producing accurate results in the full dataset.
• We were not able to examine outcomes for all racial/ethnic groups. We excluded race/ethnicities which represented less than 2% of the overall defendant population. Likewise, in order to calculate reliable percentages and predicted probabilities, we limited our analyses to groups where there were more than 50 individuals of a particular race/ethnicity.
• We were not able to tease apart guilty pleas in relation to other cases; rather, all cases resulting in a guilty plea are counted individually using the top sentence on each unique case. This likely overstates the actual use of different sentences and could impact our results if having multiple cases is not evenly distributed across racial/ethnic groups.
• While we have considered a number of individual and case-level factors in our analyses, it is not possible to consider all unique aspects of the case. For example, examining charge reduction, we have not examined the types of sentences imposed, which may impact whether a defendant received a charge reduction.
• This analysis was limited in its examination of discretion points. For example, due to lack of data, we have not examined felony declination (felony referrals not filed) and bond decisions, which prosecutors provide input on.