How Claude's values vary by model and language

Introduced a novel methodology for quantifying and analyzing the values expressed by Claude models across different contexts (models and languages). This involved developing 'value axes' (Deference vs. Caution, Warmth vs. Rigor, Depth vs. Brevity, Candor vs. Execution) derived from dimensionality reduction of observed values in conversations. The post demonstrates how these axes can characterize model behavior, showing distinct value profiles for Sonnet 4.6 and Opus 4.7, and also highlights variations in expressed values across different languages. This work provides an empirical framework for understanding how training decisions and linguistic contexts influence model output.