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规律与因果关系;概括与因果解释。

Regularities and causality; generalizations and causal explanations.

作者信息

Bogen Jim

机构信息

University of Pittsburgh, Pittsburgh, PA 15260, USA.

出版信息

Stud Hist Philos Biol Biomed Sci. 2005 Jun;36(2):397-420. doi: 10.1016/j.shpsc.2005.03.009.

Abstract

Machamer, Darden, and Craver argue (Mechanism) that causal explanations explain effects by describing the operations of the mechanisms (systems of entities engaging in productive activities) which produce them. One of the aims of this paper is to take advantage of neglected resources of Mechanism to rethink the traditional idea (Regularism) that actual or counterfactual natural regularities are essential to the distinction between causal and non-causal co-occurrences, and that generalizations describing natural regularities are essential components of causal explanations. I think that causal productivity and regularity are by no means the same thing, and that the Regularists are mistaken about the roles generalizations play in causal explanation. Humean, logical empiricist, and other Regularist accounts of causal explanation have had the unfortunate effect of distracting philosophers from important non-explanatory scientific uses of laws and lesser generalizations which purport to describe natural regularities. My second aim is to characterize some of these uses, illustrating them with examples from neuroscientific research.

摘要

马卡默、达登和克雷弗在《机制》一文中指出,因果解释通过描述产生结果的机制(参与生产活动的实体系统)的运作来解释结果。本文的目标之一是利用《机制》中被忽视的资源,重新思考传统观点(规则主义),即实际的或反事实的自然规律对于区分因果共现和非因果共现至关重要,且描述自然规律的概括是因果解释的重要组成部分。我认为因果生产力和规律性绝不是一回事,规则主义者对于概括在因果解释中所起的作用存在误解。休谟主义、逻辑经验主义以及其他规则主义对因果解释的阐释产生了不幸的影响,使哲学家们忽视了法则和旨在描述自然规律的次要概括在非解释性科学中的重要用途。我的第二个目标是描述其中一些用途,并通过神经科学研究的例子加以说明。

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