Explicating Top-Down Causation Using Networks and Dynamics. Bechtel, W. Philosophy of Science, 84(2):253–274, April, 2017. abstract bibtex In many fields in the life sciences investigators refer to downward or top-down causal effects. Craver and I defended the view that such cases should be understood in terms of a constitution relation between levels in a mechanism and intralevel causal relations (occurring at any level). We did not, however, specify when entities constitute a higherlevel mechanism. In this article I appeal to graph-theoretic representations of networks, now widely employed in systems biology and neuroscience, and associate mechanisms with modules that exhibit high clustering. As a result of interconnections within clusters, mechanisms often exhibit complex dynamic behaviors that constrain how individual components respond to external inputs, a central feature of top-down causation.
@article{bechtel_explicating_2017,
title = {Explicating {Top}-{Down} {Causation} {Using} {Networks} and {Dynamics}},
volume = {84},
issn = {00318248},
abstract = {In many fields in the life sciences investigators refer to downward or top-down causal effects. Craver and I defended the view that such cases should be understood in terms of a constitution relation between levels in a mechanism and intralevel causal relations (occurring at any level). We did not, however, specify when entities constitute a higherlevel mechanism. In this article I appeal to graph-theoretic representations of networks, now widely employed in systems biology and neuroscience, and associate mechanisms with modules that exhibit high clustering. As a result of interconnections within clusters, mechanisms often exhibit complex dynamic behaviors that constrain how individual components respond to external inputs, a central feature of top-down causation.},
number = {2},
journal = {Philosophy of Science},
author = {Bechtel, William},
month = apr,
year = {2017},
keywords = {CAUSAL models, CAUSATION (Philosophy), Causal models, Causation (Philosophy), GRANGER causality test, Granger causality test, LOG-linear models, Log-linear models, PATH analysis (Statistics), Path analysis (Statistics)},
pages = {253--274}
}
Downloads: 0
{"_id":"csiLwjCYFdPTZNGBd","bibbaseid":"bechtel-explicatingtopdowncausationusingnetworksanddynamics-2017","authorIDs":[],"author_short":["Bechtel, W."],"bibdata":{"bibtype":"article","type":"article","title":"Explicating Top-Down Causation Using Networks and Dynamics","volume":"84","issn":"00318248","abstract":"In many fields in the life sciences investigators refer to downward or top-down causal effects. Craver and I defended the view that such cases should be understood in terms of a constitution relation between levels in a mechanism and intralevel causal relations (occurring at any level). We did not, however, specify when entities constitute a higherlevel mechanism. In this article I appeal to graph-theoretic representations of networks, now widely employed in systems biology and neuroscience, and associate mechanisms with modules that exhibit high clustering. As a result of interconnections within clusters, mechanisms often exhibit complex dynamic behaviors that constrain how individual components respond to external inputs, a central feature of top-down causation.","number":"2","journal":"Philosophy of Science","author":[{"propositions":[],"lastnames":["Bechtel"],"firstnames":["William"],"suffixes":[]}],"month":"April","year":"2017","keywords":"CAUSAL models, CAUSATION (Philosophy), Causal models, Causation (Philosophy), GRANGER causality test, Granger causality test, LOG-linear models, Log-linear models, PATH analysis (Statistics), Path analysis (Statistics)","pages":"253–274","bibtex":"@article{bechtel_explicating_2017,\n\ttitle = {Explicating {Top}-{Down} {Causation} {Using} {Networks} and {Dynamics}},\n\tvolume = {84},\n\tissn = {00318248},\n\tabstract = {In many fields in the life sciences investigators refer to downward or top-down causal effects. Craver and I defended the view that such cases should be understood in terms of a constitution relation between levels in a mechanism and intralevel causal relations (occurring at any level). We did not, however, specify when entities constitute a higherlevel mechanism. In this article I appeal to graph-theoretic representations of networks, now widely employed in systems biology and neuroscience, and associate mechanisms with modules that exhibit high clustering. As a result of interconnections within clusters, mechanisms often exhibit complex dynamic behaviors that constrain how individual components respond to external inputs, a central feature of top-down causation.},\n\tnumber = {2},\n\tjournal = {Philosophy of Science},\n\tauthor = {Bechtel, William},\n\tmonth = apr,\n\tyear = {2017},\n\tkeywords = {CAUSAL models, CAUSATION (Philosophy), Causal models, Causation (Philosophy), GRANGER causality test, Granger causality test, LOG-linear models, Log-linear models, PATH analysis (Statistics), Path analysis (Statistics)},\n\tpages = {253--274}\n}\n\n","author_short":["Bechtel, W."],"key":"bechtel_explicating_2017","id":"bechtel_explicating_2017","bibbaseid":"bechtel-explicatingtopdowncausationusingnetworksanddynamics-2017","role":"author","urls":{},"keyword":["CAUSAL models","CAUSATION (Philosophy)","Causal models","Causation (Philosophy)","GRANGER causality test","Granger causality test","LOG-linear models","Log-linear models","PATH analysis (Statistics)","Path analysis (Statistics)"],"downloads":0},"bibtype":"article","biburl":"https://api.zotero.org/users/125019/collections/9E2GYVV2/items?key=kLoa7wnTHli6GanlIPhCRcV5&format=bibtex&limit=100","creationDate":"2020-01-24T22:49:23.090Z","downloads":0,"keywords":["causal models","causation (philosophy)","causal models","causation (philosophy)","granger causality test","granger causality test","log-linear models","log-linear models","path analysis (statistics)","path analysis (statistics)"],"search_terms":["explicating","top","down","causation","using","networks","dynamics","bechtel"],"title":"Explicating Top-Down Causation Using Networks and Dynamics","year":2017,"dataSources":["Tsr2deTN3TnmRRwHm"]}