computational methods

This article explains the pretrain–finetune paradigm for transformer language models and shows how applied political scientists can use it to classify political text with relatively little labeled data and modest computation. The author frames mechanisms behind pretraining and finetuning, addresses common misconceptions about costs and complexity, and demonstrates the approach by identifying toxic language in conversation threads that follow U.S. Senators’ tweets. An online tutorial accompanies the article to help nontechnical scholars adopt the workflow.

Courts can change what communities talk about and how they think about law. This study examines whether major judicial decisions shaped issue attention and attitudes toward courts in media serving the LGBTQ+ community.

Political district scores are meant to flag unfair maps, but numeric measures respond not just to map shape — they also respond to noise and to seemingly innocuous implementation choices. Measurement values are affected by both noise and the compounding effects of seemingly innocuous implementation decisions. Such issues will arise for any measure, complicating efforts to use a single metric as a legal or policy standard.