Criminal justice research often requires conversion of free-text offense descriptions into overall charge categories to aid analysis. For example, the free-text offense of "eluding a police vehicle" would be coded to a charge category of "Obstruction - Law Enforcement". Since free-text offense descriptions aren't standardized and often need to be categorized in large volumes, this can result in a manual and time intensive process for researchers. ROTA is a machine learning model for converting offense text into offense codes.

Currently ROTA predicts the Charge Category of a given offense text. A charge category is one of the headings for offense codes in the 2009 NCRP Codebook: Appendix F.

The model was trained on publicly available data from a crosswalk containing offenses from all 50 states combined with three additional hand-labeled offense text datasets.

For more information on the model, please see the model repo.

This model and application were developed by the RTI International Center for Data Science and AI.