Despite the growing utility of Large Language Models (LLMs) for simulating human behavior, the extent to which these synthetic personas accurately reflect world and moral value systems across different cultural conditionings remains uncertain. This paper investigates the alignment of synthetic, culturally-grounded personas with established frameworks, specifically the World Values Survey (WVS), the Inglehart-Welzel Cultural Map, and Moral Foundations Theory. We conceptualize and produce LLM-generated personas based on a set of interpretable WVS-derived variables, and we examine the generated personas through three complementary lenses: positioning on the Inglehart-Welzel map, which unveils their interpretation reflecting stable differences across cultural conditionings; demographic-level consistency with the World Values Survey, where response distributions broadly track human group patterns; and moral profiles derived from a Moral Foundations questionnaire, which we analyze through a culture-to-morality mapping to characterize how moral responses vary across different cultural configurations. Our approach of culturally-grounded persona generation and analysis enables evaluation of cross-cultural structure and moral variation.

翻译：尽管大语言模型在模拟人类行为方面日益实用，但这些合成人物在不同文化条件下准确反映世界和道德价值体系的程度仍不确定。本文研究了基于文化基础的合成人物与既定框架（特别是世界价值观调查、英格尔哈特-韦尔策尔文化地图和道德基础理论）的对齐情况。我们基于一组可解释的世界价值观调查派生变量概念化并生成大语言模型人物，并通过三个互补视角审视生成的人物：在英格尔哈特-韦尔策尔文化地图上的定位，揭示其反映跨文化条件稳定差异的解读；与世界价值观调查在人口统计层面的一致性，其中响应分布大致追踪人类群体模式；以及源自道德基础问卷的道德轮廓，我们通过文化到道德的映射对其进行分析，以表征不同文化配置下道德响应的变化。我们基于文化基础的人物生成和分析方法能够评估跨文化结构和道德变异。