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Pamela Oliver Presentation to Governor’s Commission May 22 2007

Pamela Oliver Presentation to Governor’s Commission May 22 2007. The Scope of the Problem & How to Measure it. Outline. National overview Compare Wisconsin to US Scatterplots Timetrends Wisconsin Trends by Admission type, race & offense County Imprisonment Patterns County Arrest Patterns

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Pamela Oliver Presentation to Governor’s Commission May 22 2007

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  1. Pamela OliverPresentation to Governor’s Commission May 22 2007 The Scope of the Problem & How to Measure it Pamela Oliver

  2. 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

  3. National Trends: The Magnitude of the Problem Pamela Oliver

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

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

  6. 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

  7. 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 ÷ 4701123 = .000217. • Multiply .00021 by 100,000 = 22, the imprisonment rate per 100,000 population. • 1,266 Blacks imprisoned, Black population of Wisconsin was 285,308. • 1266 ÷ 285308 = .004437. • 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

  8. Black and White prison admissions, historical Pamela Oliver

  9. 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

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

  11. Property Crime Pamela Oliver

  12. Violent Crime Pamela Oliver

  13. Violent Crime by Sex of Victim Pamela Oliver

  14. So what has been going on? Pamela Oliver

  15. 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

  16. Black/White RRI by type of prison admission Revocations All Admits New Sentences In Prison 1999 1982 Pamela Oliver

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

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

  19. National White Prison Sentence Rates by Offense 18 Other Theft Violent Drug Rob/burg 0 1983 1999 Pamela Oliver

  20. National Black Prison Sentences by Offense 300 Drug Rob/burg Violent Theft Other 0 1983 1999 Pamela Oliver

  21. 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

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

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

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

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  26. Pamela Oliver Black/White Disparity is not the same as the Black rate

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

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

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

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

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

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  34. Prison Admissions: National Corrections Reporting Program 1983-1999 (Hispanics not included in Black & White rates) Pamela Oliver

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  40. Pamela Oliver Note: MN counts probation revocations as new sentences while WI does not

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  43. Pamela Oliver Note: MN counts probation revocations as new sentences while WI does not

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  46. Pamela Oliver Note: MN counts probation revocations as new sentences

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  48. Pamela Oliver Disparity is different from Black rate

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  50. 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

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