People with different worldviews may have different interpretations for the same object. Freedom fighters for some are terrorists for others; immigrants can be seen as a threat or being threatened. To incorporate differences in interpretations into quantitative models, I propose the construct of value-instantiating beliefs, or perceived consequences of actions for basic human values. I hypothesize that these beliefs moderate the relationship between personal values and attitudes. In a preregistered mixed-methods study (N = 2038) I assess personal value priorities, attitudes, and perceived consequences of four political behaviours. Beliefs about consequences of the behaviours differed with political affiliation: for example, liberals saw voting for Trump in light of negative consequences for universalistic values, while conservatives stressed positive consequences for self-direction and security. The moderation hypothesis was confirmed. Including value-instantiating beliefs in the models significantly improved the predictions of attitudes towards and intentions to perform the behaviours.

中文翻译：

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关于桑德斯、特朗普和犀牛：量化主观解释有助于预测政治态度

不同世界观的人可能对同一个对象有不同的理解。对一些人来说，自由斗士对另一些人来说是恐怖分子；移民可以被视为威胁或受到威胁。为了将解释的差异纳入定量模型，我建议构建价值实例化信念，或对基本人类价值观的行为的感知后果。我假设这些信念调节了个人价值观和态度之间的关系。在一项预先注册的混合方法研究中（N = 2038）我评估了四种政治行为的个人价值优先级、态度和感知后果。对行为后果的看法因政治派别而异：例如，自由派认为投票给特朗普是因为对普遍主义价值观的负面影响，而保守派则强调对自我指导和安全的积极影响。适度假设得到证实。在模型中包含价值实例化信念显着改善了对执行行为的态度和意图的预测。