Real human agents, even when they are rational by everyday standards, sometimes assign different credences to objectively equivalent statements, such as ‘Orwell is a writer’ and ‘E.A. Blair is a writer’, or credences less than 1 to necessarily true statements, such as not-yet-proven theorems of arithmetic. Anna Mahtani calls this the phenomenon of ‘opacity’. Opaque credences seem probabilistically incoherent, which goes against a key modelling assumption of probability theory. I sketch a modelling strategy for capturing opaque credence assignments without abandoning probabilistic coherence. I draw on ideas from judgement-aggregation theory, where we face similar challenges of defining the ‘objects of judgement’.

中文翻译：

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尽管不透明，但概率上一致的可信度

真正的人类代理人，即使按照日常标准是理性的，有时也会为客观上等效的陈述分配不同的可信度，例如“奥威尔是一位作家”和“EA布莱尔是一位作家”，或者对必然真实的陈述分配小于 1 的可信度，例如作为尚未证明的算术定理。安娜·马塔尼（Anna Mahtani）将此称为“不透明”现象。不透明的信用似乎在概率上是不连贯的，这违背了概率论的一个关键建模假设。我勾勒出一种建模策略，用于捕获不透明的信任分配而不放弃概率一致性。我借鉴了判断聚合理论的思想，在该理论中，我们在定义“判断对象”方面面临着类似的挑战。