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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 afield assessment framework that we use to validate a model predicting ratinfestations in Washington, D.C. The model was developed with data from thecity's 311 service request system. Although the model performs well against new311 data, we find that it does not perform well when predicting the outcomes ofinspections in our field assessment. We recommend that data scientists expandthe use of field assessments to test their models.

A Cautionary Tail: A Framework and Case Study for Testing Predictive Model Validity