Understanding Wrongful Convictions: Research, Criteria, and Policy Interventions

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The Preventing Wrongful Convictions Project delves into the factors leading to erroneous convictions, exploring research questions, case criteria, organizational assistance, and case selection methodologies. Focusing on factual innocence, the project aims to identify near misses and provide insights to improve the criminal justice system. Supported by various organizations, the project emphasizes the need for policy interventions to prevent future wrongful convictions.


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  1. The Preventing Wrongful Convictions Project Jon Gould, Julia Carrano, and Joe Young American University With Richard Leo University of San Francisco School of Law Funded by the National Institute of Justice

  2. A Century of Investigation Edwin Borchard (1913) Bedau and Radelet (1987) DNA! (1990s) Journalists Innocence Project National Registry of Exonerations

  3. The Usual Story Eyewitness Misidentification False Confessions Junk Science Snitch Testimony Police and Prosecutorial Misconduct Poor Defense Lawyering Tunnel Vision

  4. Our Research Questions 1. Why are innocent suspects erroneously convicted in certain cases but dismissed or acquitted in others? 2. What policy interventions will help the criminal justice system get it right and prevent future erroneous convictions?

  5. Research as exploratory Research on near misses is novel Erroneous conviction literature as a guide Primarily inductive

  6. Case Criteria Defendant must be . Convicted or indicted by a state Of a violent felony against a person Post-1980 Factually innocent

  7. Factual Innocence Conservative, irrefutable definition: Official statement of innocence Convincing factual evidence of innocence

  8. Organizations that Assisted with Case Collection and Research Innocence Project Police Foundation Association of Prosecuting Attorneys National District Attorneys Association National Association of Criminal Defense Lawyers

  9. Case Selection Identifying Potential Cases Determining if Cases Meet Project Criteria 460 Included Cases 260 Erroneous Convictions 200 Near Misses

  10. The Mixed-Methods Research Process Evaluation Analysis Collection Case facts gathered through interviews, records review, databases , books, the news media Strength of evidence and strength of defense scales Chi-Square Analysis (quantitative) Logistical Regressions (quantitative) Creation of select case narratives, matched on strength of evidence Case facts recorded on narrative coding sheet Expert panel interpretation of results (qualitative) Expert panel discussion of case narratives Variables re- coded into SPSS format Policy Recommendations

  11. What Do They Have in Common? Bivariate Results False confessions Eyewitness error Crime similar to defendant s criminal history Police and prosecutor misconduct and error (except Brady) Perjury by snitch/jailhouse informant

  12. What is Not Important? Noticeably low frequencies among all cases Forensic fraud Race Abuse to elicit confession Gang membership Defense use of experts

  13. Concept Variable Coef. (Std. Err.) Death Penalty Culture 172.848** (57.809) Nature of the Crime Crime Consistency 1.086 (0.792) Female Victim 0.601 (0.463) High Profile Case -0.715 (0.486) Age -0.055** (0.027) Nature of the Defendant Black Defendant 0.213 (0.383) High School Grad -0.309 (0.483) Prior Criminal History 0.850*** (0.296) Strength of Pros. Case -1.091** (0.490) Nature of the Facts Forensic Error 0.956** (0.467) Non-eyewitness Testimony/Evidence 0.333 (0.461) Testimony Discrepancy 0.422 (0.472) Unique Perpetrator Description 0.270 (0.480) Intentional MisID -0.890** (0.448) Pros. Withheld Evidence 1.655*** (0.557) Quality of Work by CJ System Non Eyewitness Lying 1.159** (0.574) Time from Arrest to Indict 0.241 (0.493) Strength of Defense Case -1.043** (0.470) Quality of Defense Physical Alibi -0.716 (0.489) Other Suspect -0.693 (0.534) Evidence of Misconduct -0.989* (0.488) Family Witness 0.887*** (0.290) Controls Illinois Cases 0.953** (0.419) Post DNA -1.213*** (0.347) Murder Cases -0.674* (0.364) Constant -0.131 (2.111) Num. of Obs. = 460 Num. of Imputations = 5 Area Under ROC Curve = 0.908

  14. Predictor Variables--Regressions

  15. ConclusionWhat Hurts the Innocent Defendant? Death penalty culture (state punitiveness) Age (being young) Any prior criminal record Forensic errors Prosecution withholding exculpatory evidence Honest eyewitness mistakes Weak evidence by the prosecution Weak defense (just family) Lying by non-eyewitness

  16. Snitch testimony or tip False confession CJ official error Adversarial oPunitive state o Forensic error, weak facts oMistaken eyewitness, lying non-eyewitness oDefendant is older, no priors oStrong defense oProsecutor discloses Process Erroneous Conviction Near Miss

  17. What Prevents Erroneous Convictions? Checklists for investigations Forensic testing early in an investigation Stationing a prosecutor with police department Senior prosecutors assigned for intake/charging Open files discovery Threshold for line-up Post-error review Immunizing reports of error

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