Using the same linear probes trained to predict DW-Nominate scores from lawmaker-prompt activations, the authors evaluate whether they can predict the Ad Fontes political slant of 400 US news outlets when the models are prompted to generate statements from those outlets. No new probes are trained; the existing DW-Nominate probes are applied directly to the news-outlet activations. The ensembled predictions (top 32 heads) achieve Spearman correlations of 0.798 (Llama-2-7B-Chat), 0.764 (Mistral-7B-Instruct), and 0.720 (Vicuna-7B), demonstrating that the representation captures a generalizable liberal–conservative axis rather than memorized entity-specific scores.
The generalization is to US media outlets only; cross-national party ideology (411 parties) yields a much lower ρ=0.531 for Llama-2-7B-Chat, indicating the axis is US-specific.