A justice system reasonably aspires to be consistent in the application of law across cases and to account for the particulars of a case. Our goal was to create a prediction model of criminal sentence lengths that accounts for non-judicial factors such as weather and sports events among the feature set. The feature weights offer a natural metric to evaluate the importance of these features unrelated to crime relative to case-specific factors. Using a Random Forest, we found several expected crime related features appearing within the top 10% most important features. However, we also found defendant characteristics (unrelated to the crime), sport game outcomes, weather, and location features all predictive of sentence length as well, and these features were, surprisingly, more predictive than the defendant's race. Further investigating this predictive ability would be of interest to those studying the criminal justice system.
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Baseball Scores and Weather Better Predictors than Race
It's often said that race tells the tale about how you'll be treated by the criminal justice system and, in particular, about how harsh your sentence will be.
If that were true, one would expect to find at least a modest statistical correlation between race and sentencing outcomes. There was a recent study of that question, noted by Doug Berman in this entry on Sentencing Law and Policy. The last paragraph, with emphasis by Doug, is this:
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