Pamela Oliver Pamela Oliver Presentation to Governor’s Commission May The Scope of the Problem & How to Measure it

Pamela Oliver Outline  National overview  Compare Wisconsin to US  Scatterplots  Timetrends  Wisconsin Trends by Admission type, race & offense  County Imprisonment Patterns  County Arrest Patterns  Addressing the disparities  Steps in the process  Evidence at steps  Where we lack evidence

Pamela Oliver National Trends: The Magnitude of the Problem

Pamela Oliver Comparing International Incarceration Rates (Source: Sentencing Project)

Pamela Oliver World Incarceration Rates in 1995: Adding US Race Patterns

Pamela Oliver Nationally, The Black Population is Being Imprisoned at Alarming Rates  Nearly 40% of the Black male population is under the supervision of the correctional system (prison, jail, parole, probation)  Estimated “lifetime expectancy” of spending some time in prison is about 32% for young Black men.  About 12% of Black men in their 20s are incarcerated (prison + jail), about 20% of all Black men have been in prison  7% of Black children, 2.6% of Hispanic children,.8% of White children had a parent in prison in 1997 – lifetime expectancy much higher

Pamela Oliver About Rates & Disparity Ratios [Relative Rate Ratios]  Imprisonment and arrest rates are expressed as the rate per 100,000 of the appropriate population  Example: In 1999 Wisconsin new prison sentences  1021 Whites imprisoned, White population of Wisconsin was 4,701,123.  1021 ÷ =  Multiply by 100,000 = 22, the imprisonment rate per 100,000 population.  1,266 Blacks imprisoned, Black population of Wisconsin was 285,308.  1266 ÷ =  Multiply by 100,000 = 444  Calculate Disparity Ratios by dividing rates:  444/22 = 20.4 the Black/White ratio in new prison sentence rates

Pamela Oliver Black and White prison admissions, historical

Pamela Oliver Imprisonment Has Increased While Crime Has Declined  Imprisonment rates are a function of responses to crime, not a function of crime itself  Property crimes declined steadily between 1970s and 2000  Violent crime declined modestly overall, with smaller ups and downs in the period

Pamela Oliver Crime Trends Based on Bureau of Justice Statistics data from National Crime Victimization Survey.

Pamela Oliver Property Crime

Pamela Oliver Violent Crime

Pamela Oliver Violent Crime by Sex of Victim

Pamela Oliver So what has been going on?

Pamela Oliver The 1970’s Policy Shift  Shift to determinate sentencing, higher penalties  LEAA, increased funding for police departments  Crime becomes a political issue (Social turmoil & crime were high)  Drug war funding gives incentives to police to generate drug arrests & convictions: this escalates in the 1980s  Post-civil rights post-riots competitive race relations, race-coded political rhetoric.?

Pamela Oliver In Prison Revocations New Sentences All Admits Black/White RRI by type of prison admission

Pamela Oliver RRI by offense: new sentences) only Drug Rob & Burg Violent Theft Other

Pamela Oliver Rates: Black & White, drug vs other sentences

Pamela Oliver National White Prison Sentence Rates by Offense DrugRob/burg ViolentTheft Other

Pamela Oliver National Black Prison Sentences by Offense Drug Rob/burg Violent Theft Other

Pamela Oliver Drug Disparities  Nationally, Black juveniles & young adults (those under 26) use illegal drugs at LOWER RATES than White juveniles  Only among those over 25 are illegal drug use rates higher for Blacks than Whites, but the disparities are much lower than the imprisonment disparities

Pamela Oliver Black/White disparity in self-reported illegal drug use within the past year Calculated from 2003 National Survey on Drug Use & Health, Department of Health & Human Services Disparity < 1, Whites use more than Blacks Compare to prison sentence disparity of 15 at end of 1990s

Pamela Oliver Comparing Wisconsin to Other States Sources are from the Bureau of Justice Statistics

Pamela Oliver Prisons and Jails in Midyear 2005 This is “total incarceration” rate per 100,000 population

Pamela Oliver

Black/White Disparity is not the same as the Black rate

Pamela Oliver Black/White Disparity is negatively related to the White rate

Pamela Oliver In State Prisons, 1998 (This is the most recent year for which I have been able to find these data)

Pamela Oliver Note: Rates include Hispanics, who are almost all counted as White

Pamela Oliver Note: Rates include Hispanics, who are almost all counted as White

Pamela Oliver Note: Rates include Hispanics, who are almost all counted as White

Pamela Oliver

Prison Admissions: National Corrections Reporting Program (Hispanics not included in Black & White rates)

Pamela Oliver

Note: MN counts probation revocations as new sentences while WI does not

Pamela Oliver

Note: MN counts probation revocations as new sentences while WI does not

Pamela Oliver

Note: MN counts probation revocations as new sentences

Pamela Oliver

Disparity is different from Black rate

Pamela Oliver

Wisconsin vs. US Trends Summary  Steep rise in Black imprisonment rates of all types after 1988  Revocations far above average in Wisconsin. Some due to data coding differences. Much is “real.”  Drug sentences in Wisconsin are even more disparate than the nation as a whole: high Black & low White rates  Black non-drug sentences in Wisconsin are a little above average while the White sentence rate is far below average, thus yielding a high disparity.

Pamela Oliver Graphs from my analysis of Wisconsin Department of Corrections Data Wisconsin

Pamela Oliver Black AmerInd Hispanic Asian White

Pamela Oliver Proportion of Admissions Involving New Sentences (1991-9)

Pamela Oliver White Admissions Status New Sentence Only Violation Only Violation + New

Pamela Oliver Blacks Admission Status New Sentence Only Violation Only Violation + New

Pamela Oliver Black AmerInd Hispanic Asian White

Pamela Oliver Black AmerInd Hispanic Asian White

Pamela Oliver New only plus (new + violation) Black AmerInd Hispanic Asian White

Pamela Oliver Offense trends in new prison sentences by race.

Pamela Oliver Violent Rob/burg Drug Theft Other Whites 14

Pamela Oliver Blacks 300 Violent Rob/burg Drug TheftOther

Pamela Oliver Hispanics 100 Violent Rob/burg Drug Theft Other

Pamela Oliver Amer Inds 120 Violent Rob/burg Drug Theft Other

Pamela Oliver Asians 20 Violent Rob/burg Drug Theft Other

Pamela Oliver Age Patterns for Imprisonment

Pamela Oliver

White kids are more likely to use and sell illegal drugs than Black kids, but Black kids are MUCH more likely to be arrested and prosecuted for drug offenses

Pamela Oliver Incarceration Exacerbates the Effects of Racial Discrimination  Next few slides are from research by Devah Pager, earned PhD from University of Wisconsin Sociology, now professor at Princeton University  This was a controlled experiment in which matched pairs of applicants applied for entry-level jobs advertised in Milwaukee newspapers

Pamela Oliver Figure 4. The Effect of a Criminal Record on Employment Opportunities for Whites

Pamela Oliver Figure 5. The Effect of a Criminal Record for Black and White Job Applicants

Pamela Oliver Optional: Compare County Imprisonment Patterns See “County Comparisons” Presentation

Pamela Oliver Tracking disparities through the system

Pamela Oliver Rates vs. Disparities (RRI)  High RATES of incarceration are the major social problems  Costs of incarceration are tied to rates, not disparities  Disparities are higher when White rates are lower  You can lower disparities by raising White rates  Disparities are most appropriate for tracking fairness and justice within the system  Rates are most appropriate for assessing impacts on budgets and communities  Both are important, but they are not the same  Policies to reduce disparities can increase rates, and vice versa

Pamela Oliver OJA’s map of the flow through the system

Pamela Oliver My Map of the System

Pamela Oliver Decision Points Numbers indicate data sources. Green are readily available in UCR, CCAP or DOC data; light blue would be in local sources

Pamela Oliver Sentencing Commission Draft Report Focuses on sentence after adjudicated guilty of a particular offense

Pamela Oliver Sentencing Commission Study  Staff: Kristi Waits, Executive Director; Andrew Wiseman, Deputy Director; Brenda R. Mayrack, Analyst  CCAP + DOC data  Offenses committed after January 31, 2003 and sentenced before October 1, 2006  5 common offenses: sexual assault of child, sexual assault, robbery + armed robbery, burglary, drug trafficking  Sentencing for worst offense, in cases of multiple offenses

Pamela Oliver Sample sizes Notes: “Other” includes Asians + American Indians + any others; White, Black & Other exclude Hispanics.

Pamela Oliver Main Findings 1.“Legal” factors of offense severity and prior convictions have the largest effect on sentences. (As we would hope!) 2.Men are more likely than women to be sentenced to prison, controlling for all other factors. 3.Blacks & Hispanics are more likely to be sentenced to prison rather than put on probation after controls for offense type, felony class, prior convictions, number of other charges, sex, and county of sentencing. a)Race difference is larger for less serious offenses b)Race difference even comparing people with no prior convictions. 4.There is no consistent racial difference in the LENGTH of the sentence if a prison sentence is given

Pamela Oliver Regression summaries  These use multi-variable statistics to assess the impact of each factor while controlling for all other factors in the model  They show clear evidence of an overall effect of race on likelihood of being sentenced to prison, given that there is a guilty finding  Note there is a sex effect, too!

Pamela Oliver Non- drug offenses.

Pamela Oliver Drug Trafficking Offenses

Pamela Oliver Verbal summary of statistical results Statistically controlling for other factors  Blacks 47% & Hispanics 65% more likely to get a prison sentence for non-drug crimes  Blacks nearly twice as likely (196%) and Hispanics nearly 2 and a half times as likely (243%) to get a prison sentence for a drug crime  Men were 272% more likely than women to get a prison sentence for a non-drug offense and 250% more likely to get a prison sentence for a drug offense.

Pamela Oliver See report appendix for bar graphs for percentages for specific offenses (When the report is final)

Pamela Oliver Policy implications of Sentencing Study  Focus on WHETHER to give a prison sentence, not just how long a sentence should be given  Examine plea bargaining processes which often pre-determines the sentence type as well as the severity of the charged offense  Consider impact of social factors (i.e. job, marriage, home) on sentencing  Remember that a record of prior arrests & misdemeanors may be due to patterns of policing

Pamela Oliver Arrests

Crime & Arrest  MOST crime does not result in arrest!  MOST crime is relatively minor: petty theft, disorderly conduct  Arrest is a function of  Crime  Reporting of crime to police  Policing patterns & practices: WHERE you police & HOW you police  Officer decisions  Impossible to assess fairness in arrest without data on crime, which we don’t have!

Pamela Oliver Arrest Patterns ( ): Adult  (I did this analysis in the past; it can be updated)  Most arrests are for the least serious offenses & never result in incarceration  Patterns of arrests for low-level offenses contribute to prior records at sentencing  Race is officer’s perception: most probably default to White  “White” arrests include Hispanics because there is no separate Hispanic category in official arrest reports

Pamela Oliver Offense Proportions, Adult arrests “Serious” offenses include homicide, sexual assault, aggravated assault, robbery, burglary, motor vehicle theft

Pamela Oliver Adult Disparity (RRI) Ratios in Arrests

Pamela Oliver Black/White Disparities in Arrests

Pamela Oliver Adult, Total arrests

Pamela Oliver Adult Serious arrests

Pamela Oliver Adult, Other Exc Traffic arrests

Pamela Oliver Adult Drug not Marijuana arrests

Pamela Oliver Adult Marijuana Arrests

Pamela Oliver Disparity in Crime & Arrest  Some is doubtless due to real differences in crime, can be addressed only through the underlying causes of crime  Some is due to patterns of policing  Police focus on “high crime” areas  Different police jurisdictions have different racial compositions & different practices  High disparities in arrest for lesser offenses that many commit may indicate policing patterns  These give young people “prior records” that affect subsequent treatment  Drug crimes are different from other crimes: most differences in drug arrests arise from policing practices rather than differences in actual crime

Pamela Oliver Comparing Arrest and Imprisonment  Group offenses in arrest & prison sentence data so they match up  Count number of arrests by offense & race for  Count number of prison sentences by offense & race for  Ratio prison sentences to arrests is roughly chances of going to prison after arrest (i.e. post-arrest processing)  This ratio is lower for lesser offenses, higher for more serious offenses  Not matching up particular people, but overall rates  Disparity or RRI is the ratio of the ratios: are minorities more likely to end up in prison after arrest?

Pamela Oliver Wisconsin Total: Ratio of Prison Sentences to Arrests by Race & Offense

Pamela Oliver Wisconsin total: RRI Prison/Arrest Ratio

Pamela Oliver  The disparity in the prison/arrest ratio is especially high for Black drug possession cases, where it is nearly 9 to 1. This merits strong scrutiny.  Other disparities that stand out (>2) include  Black ratios for non-aggravated assault, theft & fraud, prostitution and other sex offenses, drug MDI, weapons and public order offenses;  Native American homicide, assault, arson, burglary, theft, weapons, family/child, and public order offenses; and  Asian aggravated assault, assault, and burglary cases.

Pamela Oliver Where else to look?  Charging decisions (by police & prosecutors)  Prosecution decisions  Legal defense options  Plea bargains  Sentencing  Sanctioning within prisons  Probation & Parole revocations  Custody awaiting revocation  Community reintegration: job, housing, driver’s license

Pamela Oliver Conclusions: Data, Disparities, & Rates  Data does not solve the problem BUT data tells you where to look for problems & solutions  Individual cases are complex: data look for patterns across cases where the individual details average out  Data make us accountable for our actions