首页    期刊浏览 2025年08月16日 星期六
登录注册

文章基本信息

  • 标题:Causality and Unification: How Causality Unifies Statistical Regularities
  • 本地全文:下载
  • 作者:Gerhard Schurz
  • 期刊名称:THEORIA. An International Journal for Theory, History and Foundations of Science
  • 印刷版ISSN:2171-679X
  • 出版年度:2015
  • 卷号:30
  • 期号:1
  • 页码:73-95
  • DOI:10.1387/theoria.11913
  • 语种:English
  • 出版社:UPV/EHU - University of the Basque Country
  • 摘要:Two key ideas of scientific explanation - explanations as causal information and explanation as unification - have frequently been set into mutual opposition. This paper proposes a "dialectical solution" to this conflict, by arguing that causal explanations are preferable to non-causal explanations because they lead to a higher degree of unification at the level of the explanation of statistical regularities. The core axioms of the theory of causal nets (TC) are justified because they give the best if not the only unifying explanation of two statistical phenomena: screening off and linking up. Alternative explanation attempts are discussed and it is shown why they don't work. It is demonstrated that not the core of TC but extended versions of TC have empirical content, by means of which they can generate independently testable predictions.
  • 其他摘要:Two key ideas of scientific explanation - explanations as causal information and explanation as unification - have frequently been set into mutual opposition.  This paper proposes a "dialectical solution" to this conflict, by arguing that causal explanations are preferable to non-causal explanations because they lead to a higher degree of unification at the level of the explanation of statistical regularities. The core axioms of the theory of causal nets (TC) are justified because they give the best if not the only unifying explanation of two statistical phenomena: screening off and linking up. Alternative explanation attempts are discussed and it is shown why they don't work. It is demonstrated that not the core of TC but extended versions of TC have empirical content, by means of which they can generate independently testable predictions.
  • 关键词:Unification; explanation; causality; theory of causal nets; screening off; linking up
国家哲学社会科学文献中心版权所有