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Effectiveness of New York State Sex Offender Management Policies: Are We Making Communities Safer?

Effectiveness of New York State Sex Offender Management Policies: Are We Making Communities Safer?. Jeffrey C. Sandler, Ph.D. Talk presented by the New York State Alliance of Sex Offender Service Providers March 30, 2012. Purpose: Review the Public Safety Research Literature.

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Effectiveness of New York State Sex Offender Management Policies: Are We Making Communities Safer?

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  1. Effectiveness of New York State Sex Offender Management Policies: Are We Making Communities Safer? Jeffrey C. Sandler, Ph.D. Talk presented by the New York State Alliance of Sex Offender Service Providers March 30, 2012

  2. Purpose: Review the Public Safety Research Literature • Registration and Community Notification • Existing research • The NYS offender-leveling instrument • Residency Restrictions • Civil Management

  3. Part 1:Sex Offender Registration and Community Notification

  4. Offenders in New York State • Map says 32,994 as of November 4, 2011 • Ackerman, Levenson, & Harris (in press) wanted to know how many were actually in the community • Examined the number of registered sex offenders in five states, including NYS • Took out offenders not in the community (i.e., living out of state, dead, civilly committed, and/or deported) • Were left with 15,950 in the community in NYS

  5. Legislative History • Jacob Wetterling Crimes Against Children and Sexually Violent Offender Registration Act (1994) • Megan’s Law (1996) • Pam Lychner Act (1996) • New York State’s Sex Offender Registration Act (SORA; 1996) • Campus Sex Crimes Prevention Act (2000) • Adam Walsh Child Protection and Safety Act (2006)

  6. Research on the Impact of Sex Offender Registration and Notification: Evaluations using Offenders • Schram & Milloy (1995): No significant difference in re-arrest rates between registered (n = 90) and unregistered (n = 90) sex offenders in Washington State • Adkins, Huff, & Stageberg (2000): No significant difference in sexual reconviction between 201 sex offenders released in Iowa prior to registration enactment and 233 sex offenders subject to notification (sexual reconviction rates of 3.5% and 3.0%, respectively)

  7. Research on the Impact of Sex Offender Registration and Notification: Evaluations using Offenders (cont.) • Duwe & Donnay (2008): Examined the impact of community notification using a notification group (n = 155), a pre-notification group (n = 125), and a non-notification group (n = 155) in Minnesota and found notification to significantly reduce odds of sexual recidivism • Freeman (in press): NYS sex offenders subject to notification were re-arrested more quickly and at a higher rate for sexual offenses than those not subject to notification requirements after controlling for supervision effects

  8. Research on the Impact of Sex Offender Registration and Notification:Evaluations using Crime Rates • Barnoski (2005): • Findings: • Rates of sexual felony recidivism dropped after 1990 passage of registration law • Rates of sexual felony and violent felony recidivism dropped after 1997 amendment of the notification law • Study limitations: • Like the previous studies, only looked at recidivisms • Only examined rates through percentage comparisons and binary logistic regression, so ignored natural changes in the crime rate

  9. Research on the Impact of Sex Offender Registration and Notification:Evaluations using Crime Rates (cont.) • Walker, Maddan, Vásquez, VanHouten, & Ervin-McCarthy (2005): • Findings: • Six states experienced no change in rape arrest rates • Three states experienced a drop in rape arrest rates • One state experienced an increase in rape arrest rate • Study Limitations • Used UCR data: Could not separately model recidivisms, first time offenses, or different sex offenses • Modeled no non-sexual offense series for comparison

  10. Research on the Impact of Sex Offender Registration and Notification:Evaluations using Crime Rates (cont.) • Zgoba, Witt, Dalessandro, & Veysey (2008) • Findings: • Statewide sexual offense rates steadily decreased from 1985 to 2005 • No consistent effect of Megan’s Law at county level • Costs an average of about $265,000 per county per year to maintain the registry (mostly for staff) • Limited effect of Megan’s Law may not justify expense • Study Limitations: • Used UCR data: Could not separately model recidivisms, first time offenses, or different sex offenses

  11. Using a New York State SampleDoes a Watched Pot Boil? A Time-Series Analysis of New York State’s Sex Offender Registration and Notification Law Jeffrey C. Sandler Naomi J. Freeman Kelly M. Socia Article published in: Psychology, Public Policy, and Law (2008), 14, 284-302

  12. Goals of the Study • An empirical time-series analysis of the impact of New York State’s 1996 Sex Offender Registration Act (SORA) • An attempt to understand how SORA’s enactment influenced arrests rates • An attempt to investigate how different types of offending were impacted

  13. Data • Two hundred and fifty-two months (21 years) of statewide individual-level arrest data from 1986 [10 years before SORA] to 2006 [11 years afterward] • Aggregated to the state level • Included every sexual offense arrest [and therefore every sex offender arrested] during that time • Over 170,000 sexual offenses • Over 160,000 different sex offenders

  14. Test (9) Registerable sex offenses (RSOs) Total Recidivisms First time sex offenses Rapes Total Recidivisms First time sex offenses Child molestations Total Recidivisms First time sex offenses Comparison (8) Within group (sex offenders) Assaults Robberies Burglaries Larcenies Outside group (statewide) Assaults Robberies Burglaries Larcenies Series Modeled

  15. RSO Arrest Counts

  16. Results:Basic offending statistics • Most sexual offenses committed by first time sex offenders (i.e., were not sexual recidivisms) • Total RSOs: 95.88% • Rapes: 95.94% • Child molestations: 94.12%

  17. Results:Interrupted ARIMA • All test and comparison series were found to be ARIMA (0,1,1)(0,1,1)12 models • Test series: No significant change (increase or decrease) in the number of monthly arrests in any of the sexual offense series

  18. Discussion • Limitations • Arrest and re-arrest only a proxy measures for offending • Were not able to account for sex offenses committed in another state • Conclusions • No evidence that registration and community notification laws impacted rates of sexual offending • Given that the vast majority of sexual arrests are of first time (i.e., unconvicted) sex offenders, public policies that target convicted sex offenders may be limited in their ability to significantly reduce sexual offenses

  19. Research on the Impact of Sex Offender Registration and Notification:Evaluations using Crime Rates (cont.) • Letourneau, Levenson, Bandyopadhyay, Armstrong, & Sinha (2010) • Findings: • A significant reduction in adult sexual offending following the enactment of South Carolina’s sex offender registry • No significant impact on sex offenses following the enactment of South Carolina’s internet notification • Study Limitations: • Only looked at first time offenses • Did not separately model different sexual offense types

  20. Research on the Impact of Sex Offender Registration and Notification:Evaluations using Crime Rates (cont.) • Prescott & Rockoff (2011) • Findings: • Reduced sexual offenses associated with: • Broad registration without notification • Only of cases when the victim knew offender (not stranger cases) • Reduced sexual offenses associated with notification when applied narrowly…but increases when applied broadly • Study Limitations: • Used NIBRS data: Could not identify recidivisms/first time offenses, findings subject to reporting changes • Had big holes in their “registry size” variable

  21. Research on the Impact of Sex Offender Registration and Notification:Evaluations using Crime Rates (cont.) • Agan (2011) • Findings: • No significant impact associated with registry or notification enactment • No significant difference in sexual recidivism rates for offenders released before and after enactment • No relationship between the number of registered sex offenders living in an area and sexual abuse rates • Study Limitations: • Used UCR data • Had big holes in her “registry size” variable

  22. Why No Impact in New York? • Way the public is using registry and notification information is limiting the potential impact

  23. Research on the Public and Registration and Notification • Phillips (1998): • More than 60% of community members believed registration and notification encouraged sex offenders to behave better • Over 50% of respondents: • No change in leaving children with babysitter or unsupervised • No less likely to go out alone • No change in level of community involvement

  24. Research on the Public and Registration and Notification (cont.) • Anderson & Sample (2008): • Almost 90% of respondents aware of the registry • Only 35% had accessed it • Over 60% of community members report taking no preventative measures • The most common preventative measure taken was to pass the information along to • Children • Neighbors

  25. Research on the Public and Registration and Notification (cont.) • Kernsmith, Comartin, Craun, & Kernsmith (2009) • Over 94% of respondents aware of the registry • Only 37% had accessed it: Families with young children most likely (59%) • Sex offenders found to live in 99% of zip codes • Only 27% of all respondents believed an offender lived their community • Of those respondents who had accessed the registry, 51% believed an offender lived in their community

  26. Research on the Public and Registration and Notification (cont.) • Sample, Evans, & Anderson (2011): • A study of internet registry access specifically (which the authors feel is a more true test of the impact of community notification than recidivism) • About 17% of the sample accessed the registry for safety reasons • About 14% got their registry information from other sources • Did a bunch of regression analyses, but the methodology was questionable

  27. Why No Impact in New York? • Way the public is using registry and notification information is limiting the potential impact • The way New York State operates its registry and notification is limiting the potential impact • May be an artifact of the system’s structure: • Letourneau et al. (2010) – Different (more broad) system • Prescott & Rockoff (2011) – Registration should be broad, but notification needs to be narrow • May be that SORA levels are not truly indicative of sexual recidivism risk • The instrument has never been validated since its inception (Guidry, 2004)

  28. SORA risk-leveling instrument • Intended to assess two things: • Likelihood of an offender sexually recidivating (risk) • Seriousness of the offense if the offender sexually recidivates (harm) • Developed shortly after the passage of SORA • Before much research on sex offender risk was available (e.g., Hanson & Bussiére, 1998) • Before many sex offender-specific risk assessment measures were available (e.g., the Static-99)

  29. SORA risk-leveling instrument • Contains 15 items within four categories: • Current offense(s) • Criminal history • Post-offense behavior • Release environment • Various weights given to each item • Generates a total score ranging from 0 to 300, which corresponds to a level designation • Allows for the possibility of an override

  30. SORA risk-leveling items • Current offense(s): • Use of violence • Sexual contact with victim (e.g., over vs. under clothing) • Number of victims • Duration of offense conduct with victim • Age of victim • Other victim characteristics (e.g., mentally disability) • Relationship with victim

  31. SORA risk-leveling items • Criminal history: • Age at first sex crime • Number and nature of prior crimes • Recency of prior felony or sex crime • Drug or alcohol abuse • Post-offense behavior: • Acceptance of responsibility • Conduct while confined/supervised • Release environment • Supervision • Living/employment situation

  32. SORA risk-leveling instrument • Risk level assignment from score: • 0-70 = Level 1 • 75-105 = Level 2 • 110-300 = Level 3 • Four possible reasons for override (presumes a Level 3 designation) if the offender: • Has a prior felony sex conviction • Inflicted serious physical injury or death • Made recent threat to re-offend sexually/violently • Has an abnormality that hinders his/her ability to control impulsive sexual behavior

  33. SORA risk-leveling instrument • According to the website of the New York State Division of Criminal justice Services (DCJS): • 39% of all offenders are designated as Level 1 • 36% of all offenders are designated as Level 2 • 25% of all offenders are designated as Level 3 • As stated earlier, there has been no validation of the SORA risk-leveling instrument since its inception

  34. Study Goals • Investigate the predictive validity of the SORA risk levels: • Risk of sexual re-arrest • Harm of sexual re-arrest • Investigate how the SORA risk levels compare to other predictors of sexual recidivism

  35. Method: Data and Analyses • Data: A sample of 3,633 sex offenders • Registered in New York State as of August 2005 • With 5 years of post-release follow up (study censor date was January 2007) • Analyses: • Basic frequencies and descriptives to examine both risk and harm • Receiver operating characteristic area under the curve (AUC) to test predictive accuracy • Ranges from 0.0 to 1.0 (AUC = 1.0 means perfect prediction) • Prediction no better than chance is AUC = .50

  36. Method: Study Variables • Outcome variables: • Risk: Sexual re-arrest within 5 years of release (no/yes)? • Harm: New York State penal code arrest class (misdemeanor/felony)? • Independent (predictor) variables: • SORA risk levels: Those actually assigned (e.g., after overrides) • Variables empirically-related to recidivism

  37. Method: Comparison Models • Wanted to keep them simple and straightforward: • Model 1: • Age at release • Prior RSO arrests • Variety of offense types • Model 2: • Age at release • Prior RSO arrests • Variety of offense types • Stranger victim

  38. Method: Analytic Strategy • Comparison models: • Randomly split the sample in two: • Developmental dataset (n = 1,831) • Validation dataset (n = 1,802) • Generate risk models using logistic regression with sexual recidivism within 5 years as the dependent variable on the developmental dataset • Test the predictive accuracy of the models on the validation dataset • Assigned 39%, 36%, and 25% of offenders to Levels 1, 2, and 3, respectively

  39. Results: Risk 5-Year Sexual Re-Arrest Rates Level 1 2 3 SORA Levels 5.9% 6.5% 10.8% Model 1 3.5% 7.9% 13.6% Model 2 3.5% 6.8% 15.4%

  40. Results: Risk

  41. Results: Risk Predictive Accuracy Level SORA Levels Model 1 Model 2 AUC .572 .646 .667 95% CI .537 - .607 .600 - .692 .620 - .713

  42. AUC Results: Assigned SORA level

  43. AUC Results: Model: Age, RSO Arrests, Variety

  44. AUC Results: Model: Age, RSO Arrests, Variety, Stranger

  45. Results: Harm Felony Sexual Re-Arrest Rates Level 1 2 3 SORA Levels 51.7% 60.5% 65.4% Model 1 58.5% 59.6% 65.4% Model 2 59.6% 56.2% 67.2%

  46. Results: Harm Predictive Accuracy Level SORA Levels Model 1 Model 2 AUC .543 .534 .548 95% CI .473 - .613 .464 - .604 .478 - .617

  47. Results: Harm • Rethought harm variable • Recoded it to be continuous (i.e., B misdemeanor through A-1 felony) • Analyzed its correlation to the various risk levels Level SORA Levels Model 1 Model 2 Correlation to Harm .092 .109 .138 p .125 .068 .021

  48. Discussion • Limitations • Re-arrest only a proxy measure for re-offending • Official arrest offense class is only a proxy measure for seriousness of the sexual arrest • Conclusions • Risk • Assigned SORA risk levels do significantly predict 5-year sexual re-arrest • Using logistic regression and just a few variables, it’s possible to significantly improve risk prediction above SORA levels • Harm • SORA risk levels do not significantly predict sexual re-arrest offense class, whether coded dichotomously or continuously • One of the logistic models did significantly predict continuous sexual re-arrest offense class

  49. Summary:Registration and Notification • Majority of research has found no significant, systematic impact of the policies, however: • Some emerging evidence of sexual crime reduction associated with registration • Some emerging evidence of sexual crime increase associated with broad notification • No research to support the ability of registration and/or notification to reduce child molestations

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