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的实用性日益增强，但这些合成人物角色在多大程度上能准确反映不同文化背景下的世界观与道德价值体系仍不确定。本文研究了基于文化背景的合成人物角色与既有框架——特别是世界价值观调查、英格尔哈特-韦尔策尔文化地图以及道德基础理论——之间的对应关系。我们基于一组可解释的世界价值观调查衍生变量，对大语言模型生成的人物角色进行概念化构建，并通过三个互补视角进行检验：在英格尔哈特-韦尔策尔地图上的定位，揭示了其表征文化背景间稳定差异的解读；与世界价值观调查在人口统计层面的吻合度，其响应分布大体遵循人类群体模式；以及通过道德基础问卷导出的道德特征剖面，我们通过文化到道德的映射分析，刻画了不同文化配置下道德响应的变化模式。我们这种基于文化背景的人物角色生成与分析方法，为评估跨文化结构与道德变异提供了有效途径。