A Causal Bayes Net Analysis of Glennan’s Mechanistic Account of Higher-Level Causation (and Some Consequences)

Abstract

One of Glennan’s ([1996]) most prominent contributions to the new mechanist debate consists in his reductive analysis of higher-level causation in terms of mechanisms. In this article I employ causal Bayes nets (CBNs) to reconstruct his analysis. This allows for identifying general assumptions that have to be satisfied to get the analysis working. I show that once these assumptions are in place, they imply (against the background of the CBN machinery) that higher-level causation indeed reduces to interactions between component parts of mechanisms. I also briefly discuss the plausibility of these assumptions and some consequences for the mechanism debate.

Free Will, Control, and the Possibility to do Otherwise from a Causal Modeler’s Perspective

“…We would also like to emphasize that we do not subscribe to an interventionist interpretation of causation according to which causation is characterized or even defined (see, e.g., Woodward 2003) in terms of interventions. 8 Because interventions are not required for the endeavor of this paper and since how exactly interventions into the kind of mixed systems we are interested in work is still controversial (see, e.g., Baumgartner 2010Baumgartner , 2013Gebharter 2017aGebharter , 2019Woodward 2015), we prefer an understanding of causation in line with Spirtes et al (1993) in this paper.…”

“…For a proof, see(Schurz and Gebharter 2016, Theorem 2). 11 The same productivity test is used in(Gebharter 2017a) to investigate the possibility of mental causation to the background of causal exclusion worries and in(Gebharter 2019) to explore the reducibility of higher-level and inter-level causation in the presence of mechanistic hierarchies.…”