Causal Pluralism and Causal Inference, with Applications to Health and Status

现在有许多明显相互竞争的因果关系的哲学解释，每一个都提出了一种特殊的特权方法来检验因果关系；这些方法中的每一种都可以在今天的科学领域中找到。本项目认为，这些账户并非真正具有竞争性。相反，它们被用来描述以不同方式运作的不同类型的因果系统，或者回答不同类型的因果问题。美国国家科学基金会科学与技术研究学者研究奖旨在描述因果系统的类型和给定方法适合的问题，特别关注在干预下寻找因果关系不变性的方法。它是在试图了解健康不良与低社会经济地位之间显著相关性的因果关系的特殊背景下这样做的。因果研究方法的改进带来了更可靠的结果，我们可以以此为基础制定更好的政策。这不仅适用于项目中研究的健康和地位问题，而且适用于整个社会经济问题。没有一项方法学研究或少数几项研究能产生巨大影响。但是，在理解因果关系和改进因果推理方法方面，一个协调一致的、持续的努力应该会改善研究结果，这是拟议的研究应该做出的贡献；更好的研究结果应该意味着更健全的规划和政策。

There are a number of apparently competing philosophical accounts of causality now, each suggesting a particular privileged method for testing for causality; and each of these methods can be found in use across the sciences today. This project argues that these accounts are not genuinely competing. Rather, they are geared to describe different kinds of causal systems operating in different ways or to answer different kinds of causal questions. This NSF Science and Technology Studies Scholars Research Award aims to characterize the kinds of causal systems and question to which a given method is appropriate, focusing particularly on methods that look for invariance of causal relations under intervention. It does so in the special context of the attempt to understand the causal story responsible for the striking correlations between ill health and low socio-economic status. Improvements in methods for causal research lead to more reliable results on which we can base better policy. This is true not only for questions of health and status of the kind studied in the project, but across socioeconomic issues. No one methodological study or handful of studies will make dramatic impact. But a concerted, continuing effort to understand causality and to improve methods for causal inference, to which the proposed research should contribute, should improve research results; and better research results should mean sounder planning and policy.