On the Limits of Causal Modeling: Spatially-Structurally Complex Biological Phenomena.
This article examines the adequacy of causal graph theory as a tool for modeling biological phenomena. I argue that the causal graph approach reaches its limits when it comes to modeling biological phenomena that involve complex spatial and chemical-structural relations. Using a case study from mole...
| Publicado en: | Philosophy of Science Vol. 83; no. 5; pp. 921 - 934 |
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| Formato: | Artículo |
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Cambridge University Press
Dec2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=119504369&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 119504369 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00318248 PSC jtl: Philosophy of Science issn: 00318248 maglogo: N pubinfo: dt: Dec2016 vid: 83 iid: 5 pid: 15979 pub: Cambridge University Press artinfo: ui: 119504369 10.1086/687875 ppf: 921 ppct: 13 formats: fmt: – @attributes: type: T – @attributes: type: P size: 787KB tig: atl: On the Limits of Causal Modeling: Spatially-Structurally Complex Biological Phenomena. aug: au: Kaiser, Marie I. affil: This paper arose from a collaboration with Marcel Weber during my time at the University of Geneva, and it profited much from our stimulating discussions. I also thank Benjamin Jantzen, Christopher Hitchcock, Lorenzo Casini, Alexander Gebharter, Maximilian Huber, and the members of my DFG Research Group "Causation and Explanation" for their helpful comments on earlier versions of the paper. This material is based on work supported by the German Research Foundation. To contact the author, please write to: Philosophisches Seminar, Universität zu Köln, Richard-Strauß-Str. 2, 50931 Köln, Germany su: Causal models Spatial data structures Graph theory Bayesian analysis Causation (Philosophy) sug: subj: Causal models Spatial data structures Graph theory Bayesian analysis Causation (Philosophy) ab: This article examines the adequacy of causal graph theory as a tool for modeling biological phenomena. I argue that the causal graph approach reaches its limits when it comes to modeling biological phenomena that involve complex spatial and chemical-structural relations. Using a case study from molecular biology, I show why causal graph models fail to adequately represent and explain biological phenomena of this kind. The inadequacy of these models is due to their failure to include relevant spatial-structural information in a way that does not render the models nonexplanatory, unmanageable, or inconsistent with basic assumptions of causal graph theory. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Copyright of Philosophy of Science is the property of Cambridge University Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. item: Philosophy of Science holder: Cambridge University Press dt: @attributes: year: 2016 holdings: @attributes: islocal: N |
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