• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Philosophical Transactions of the Royal Society of London, Series B. Biological Sciences >Network explanations and explanatory directionality
【24h】

Network explanations and explanatory directionality

机译：网络解释和解释性方向性

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Network explanations raise foundational questions about the nature of scientific explanation. The challenge discussed in this article comes from the fact that network explanations are often thought to be non-causal, i.e. they do not describe the dynamical or mechanistic interactions responsible for some behaviour, instead they appeal to topological properties of network models describing the system. These non-causal features are often thought to be valuable precisely because they do not invoke mechanistic or dynamical interactions and provide insights that are not available through causal explanations. Here, I address a central difficulty facing attempts to move away from causal models of explanation; namely, how to recover the directionality of explanation. Within causal models, the directionality of explanation is identified with the direction of causation. This solution is no longer available once we move to non-causal accounts of explanation. I will suggest a solution to this problem that emphasizes the role of conditions of application. In doing so, I will challenge the idea that sui generis mathematical dependencies are the key to understand non-causal explanations. The upshot is a conceptual account of explanation that accommodates the possibility of non-causal network explanations. It also provides guidance for how to evaluate such explanations.
机译：网络解释提出了关于科学解释性质的基础问题。本文中讨论的挑战来自于，网络解释通常被认为是非因果的事实，即它们没有描述对某些行为负责的动态或机制互动，相反，他们吸引了描述系统的网络模型的拓扑属性。这些非因果特征通常被认为是有价值的，因为它们不援引机械或动态相互作用，并提供通过因果解释没有提供的见解。在这里，我解决了远离解释的因果模型的尝试难度难度;即，如何恢复解释的方向性。在因果模型中，以因果的方向识别解释的方向性。一旦我们转移到解释的非因果账户，就不再提供该解决方案。我会建议解决这个问题的解决方案，强调了应用条件的作用。在这样做时，我会挑战Sui Generis数学依赖性是了解非因果解释的关键。 upshot是一个概念解释，其适应非因果网络解释的可能性。它还提供了如何评估此类解释的指导。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号