Preventing Wrongful Convictions Project
The Preventing Wrongful Convictions Project, led by Dr. Jon Gould and funded by the National Institute of Justice, is a unique collaboration between academic researchers and criminal justice professionals, including representatives of the prosecutorial and defense communities. The goal of the project is to understand how the criminal justice system avoids wrongful convictions by determining what factors or uniquely present in violent felony cases that ended in an official exoneration after conviction (“erroneous convictions”) with those in which defendants had charges dismissed before trial or were acquitted on the basis of their factual innocence (“near misses”).
Our research began by identifying a set of 460 erroneous conviction and near miss cases that met a stringent definition of innocence. We then researched and coded the cases along a number of variables, including location effects, nature of the victim, nature of the defendant, facts available to the police and prosecutor, quality of work by the criminal justice system, and quality of work by the defense. The cases were subsequently analyzed using bivariate and logistic regression techniques. With the assistance of an expert panel, we also explored the cases from a qualitative perspective.
Project Results
The results indicate that 10 factors help explain why an innocent defendant, once indicted, ends up erroneously convicted rather than released. These include:
- age and criminal history of the defendant
- punitiveness of the state
- Brady violations
- forensic error
- inadvertent misidentification
- lying by a non-eyewitness
- weak prosecution and defense case
- family defense witness
Other factors traditionally suggested as sources of erroneous convictions, including false confessions, criminal justice official error, and race effects, appear in statistically similar rates in both sets of cases; thus, they likely increase the chance that an innocent suspect will be indicted but not the likelihood that the indictment will result in a conviction. Finally, our qualitative review of the cases reveals how the statistically significant factors are connected and exacerbated by tunnel vision, which prevents the system from self-correcting once an error is made. In fact, tunnel vision provides a useful framework for understanding the larger system-wide failure that separates erroneous convictions from near misses.
