Works in Progress
I have been working on a number of research projects. This work falls under the general heading of the “dynamics of offender risk.” The issues fall into three categories, theoretical, methodological, and practical.
First, I am working to explore the mathematical relationship between criminal propensity, criminal sanction processes, and the crime rate. It would appear that the relationship between these three variables is nonlinear. This seems to have some important consequences for the study of population levels of crime.
Next, I am interested in the study of the age crime curve and the development of criminal behavior over the life course. I am working on a developmental theory that proposes that the age crime curve is caused by developmental timing of physical and mental development over the life course. In this model, physical capacity grows first, and peaks at about age 25. Mental capacity does not peak until about five years after physical capacity at about age 30. This difference in the peak age of development causes a “maturity gap” (Moffitt, 1993). The maturity gap would explain why crime rises from almost nothing to peak in late adolescence and early adulthood, and then decline until few people commit crimes in later adulthood.
Finally, I am interested in the trait and state aspects of criminal propensity. I have been working with multi-wave sets of risk assessment scores that track offender recidivism risk over time. The two primary datasets include about 3,000 sets of Level of Service Inventory-Revised (LSI-R) scores from offenders on probation in a Midwestern county and 40,000 sets of Offender Assessment System (OASys) scores out of England. These data seem to suggest that there is both stability and change in offender risk levels. I am working to integrate this material so that it can be used to build better risk assessment methods.
The literature on risk assessment has established that offender risk is “dynamic.” However, there has been very little work that examines the “dynamics of offender risk.” There are several issues that would seem to need to be addressed.
First, there is a possible problem with rater error in risk assessment. We need to ask, “What is changing when risk scores change?” It could be something other than risk levels. My research suggests that offender rating may be changing over time, and this is making it difficult to measure the true levels of offender change. We need to look at how error structures change over time and fix faulty assessment tools.
Second, we need to know more about how Trait and State risk factors are related. Offender risk is dynamic and includes both stable (trait) and unstable (State) components. That means that a person’s risk of offending will change over time as both Traits and States change. Some of any observed change is due to an actual change in Trait and some is due to a temporary change in State. This dual nature of offender risk has important consequences for the study of offender risk and ultimately for offender treatment studies. I am working on methods such as the Reliable Change Index (RCI) and individual growth curve modeling to address some of these problems.
Third, we need to determine how physical and mental development affect risk levels. It would seem that strength is not assessed in current attempts at risk assessment, and yet it could have important effects on the level of offender risk. In addition, greater emphasis needs to be placed on mental development. Intelligence is not static. It changes over time in a predictable way. We need to pay more attention to developmental factors as we work with offenders.
Finally, should research focus on group experiments or single case, time series designs? I have been working on some methods for individual growth curve modeling that could help probation officers track the risk levels of individual offenders.
The last category has to do with the issues related to assessment. It would seem that assessment has to be ongoing. The current practice of performing comprehensive risk assessments once or twice per year would seem to be inadequate. The assessment process should be automated so that it fits seamlessly into the day to day operations of the corrections departments. The data analysis should be done in real time so that risk of offending can be minimized.