#frAIday: Transformer-based variables for estimating hate crimes in police reports

To address the challenge of estimating population totals in large textual datasets within official statistics, where manual annotation is impractical, we propose a method combining transformer encoder neural network predictions and well-established survey sampling estimators. This is done by training a classifier and then using the model predictions as an auxiliary variable in the estimators. The applicability is demonstrated on Swedish hate crime statistics, which are based on Swedish police reports, for which approximately 1.5 million are being filed annually.