The discovery of causal relations seems a central activity of the high-level sciences, including the special sciences and certain branches of macrophysics. Those same sciences are less successful in formulating exceptionless laws. If causation must be underwritten by exceptionless laws, we are faced with a puzzle. Attempts have been made to dissolve this puzzle by showing that non-exceptionless generalizations can underwrite causal relations. The trouble is that many of these attempts fail to distinguish between two importantly different types of exception of which high-level scientific generalizations admit. Roughly speaking, one is where the values of high-level variables not represented in the generalization are abnormal: call these 'background factor' (bf) exceptions. For example, the Ideal Gas Law (IGL) may be significantly violated by a gas if a strong electric current is passed through it. Another is where the high-level states that are represented by variables in the generalization are realized in certain abnormal ways: call these 'mr exceptions' (exceptions having to do with the multiple realizability of high-level states). For example, the pressure of a gas may not be proportional to its temperature and volume in the way that the IGL describes if the initial macrostate of the gas is realized in a certain unusual microphysical way. While existing attempts to show that non-exceptionless generalizations can underwrite causal relations tend to work well where the generalization admits only of bf exceptions, they work less well when the generalizations in question admit—as most high-level scientific generalizations do—of mr exceptions. I argue that the best prospect for resolving the apparent problem posed by mr exceptions is to regard the generalizations which admit of them as approximations to probabilistic generalizations which don't, and which are themselves able to support relations of probabilistic causation.

中文翻译：

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有高层次的因果关系吗？

因果关系的发现似乎是高级科学的中心活动，包括特殊科学和宏观物理学的某些分支。那些相同的科学在制定例外法律方面不太成功。如果必须由例外法律来支持因果关系，那么我们将面临一个难题。试图通过证明非例外的概括可以掩盖因果关系来解决这个难题。麻烦在于，这些尝试中的许多尝试都无法区分两种重要的不同类型的例外，高级科学概括却承认这两种例外。粗略地说，一种情况是泛化中未表示的高级变量的值异常：将这些称为“背景因素”（bf）异常。例如，如果强电流通过，可能会严重违反理想气体定律（IGL）。另一个是在概括中用变量表示的高级状态是以某些异常方式实现的：将这些称为“ mr异常”（与高级状态的多重可实现性相关的例外）。例如，气体的压力可能不像IGL描述的那样以某种不常见的微物理方式实现气体的初始宏观状态，而与温度和体积成正比。尽管现有的尝试表明非例外的概括可以承保因果关系，但在归纳只允许bf例外的情况下，这种方法往往会奏效，当所讨论的概括（如大多数高级科学概括所接受的）承认先生例外时，它们的工作效果就会变差。我认为，解决先生例外所带来的明显问题的最佳前景是，将承认其为例外的概化看作是不能归纳的概率归纳的近似，它们本身也能够支持概率因果关系。