  Data scientists frequently train predictive models on administrative data.
However, the process that generates this data can bias predictive models,
making it important to test models against their intended use. We provide a
field assessment framework that we use to validate a model predicting rat
infestations in Washington, D.C. The model was developed with data from the
city's 311 service request system. Although the model performs well against new
311 data, we find that it does not perform well when predicting the outcomes of
inspections in our field assessment. We recommend that data scientists expand
the use of field assessments to test their models.
