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Escapes from Custody and Violence: A Critical Analysis

Escapes from Custody and Violence: A Critical Analysis. Bryce E. Peterson Adam G. Fera Jeff Mellow John Jay College/CUNY Graduate Center. Introduction. Armed Criminal Career Act (ACCA) of 1984 Firearm conviction + 3 prior violent felonies = 15 years Crime is violent if it

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Escapes from Custody and Violence: A Critical Analysis

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  1. Escapes from Custody and Violence: A Critical Analysis Bryce E. Peterson Adam G. Fera Jeff Mellow John Jay College/CUNY Graduate Center

  2. Introduction • Armed Criminal Career Act (ACCA) of 1984 • Firearm conviction + 3 prior violent felonies = 15 years • Crime is violent if it • has an element the use, attempted use, or threatened use of physical force against the person of another, or • is burglary, arson, or extortion, involves the use of explosives, or otherwise involves conduct that presents a serious potential risk of physical injury to another.

  3. Are escapes violent? • U.S. Courts of Appeal and USSC say YES! • Chambers v. U.S., 555 U.S. 122 (2009) • Failure to report does not qualify as violent felony • Distinct from “escape” “[E]very escape scenario is a powder keg, which may or may not explode into violence…” (U.S. v. Gosling, 1994)

  4. Escape Research • Limitations of previous research • Old research • Non-rigorous studies • Intra-state trends, prisons, and in-facility escapes • No central definition of “escape” • Circuit Courts and USSC called for more research • Sentencing Commission (2008) • Violence: Overall, during escape, during recapture • Found: secure escapes have more violence • Limitations: federal prisons, few factors

  5. The Current Study • Examine the role of violence in prison escapes • Major objectives • Identify facility, inmate, and suspect-level factors associated with violent escapes from custody • Examine violence overall, during the incident, post-incident, and during recapture. • Create and test a predictive model of violent escapes

  6. Data • Correctional Incident Database (2009) • Rigorous open-source search protocol (Freilich & Chermak, ECDB) • Facility, incident, and suspect data • Escapes: a loss of correctional control over an inmate in custody

  7. Analytic Approach Steps • Analyze descriptive statistics • Identify trends • Create a predictive model of violent escapes using bivariate analyses • Test model using logistic regression

  8. Escapes from Custody:Correctional Incident Database • Total numbers (2009) • 608 suspects, 501 incidents, 400 facilities • Current Study • 270 suspects, 223 incidents, 198 facilities

  9. Facility Classification by Overall Violence

  10. Custody & Location by Overall Violence

  11. Other Factors • Other significant associations • Assistance received, plan, violent record, male facility, staff to inmate ratio, private facility, start time • Insignificant associations • Season, day of week, facility age, ACA accreditation, suspect age, race, gender, property record, percent capacity, adult facility

  12. Discussion • Not much violence overall • Especially in non-secure settings • Data are biased TOWARD violence • Certain factors may lead to violence • Outside, secure custody, planning, violent records • Not all violence is equal • “shoving” ≠ murder

  13. Conclusions • Implications • Longer sentences for inmates • Cost of incarceration • Overcrowding • Other sentencing enhancements • Future Research • More data collection • Violence at different points • Seriousness of violence

  14. Contact info • Bryce Peterson – bpeterson@jjay.cuny.edu • Adam G. Fera- afera@jjay.cuny.edu • Jeff Mellow – jmellow@jjay.cuny.edu

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