@article {clarke2014modelling,
	title = {Modelling mechanisms with causal cycles},
	journal = {Synthese},
	volume = {191},
	number = {8},
	year = {2014},
	pages = {1651{\textendash}1681},
	abstract = {<p>Mechanistic philosophy of science views a large part of scientific activity as engaged in modelling mechanisms. While science textbooks tend to offer qualitative models of mechanisms, there is increasing demand for models from which one can draw quantitative predictions and explanations. Casini et al. (Theoria 26(1):533, 2011) put forward the Recursive Bayesian Networks (RBN) formalism as well suited to this end. The RBN formalism is an extension of the standard Bayesian net formalism, an extension that allows for modelling the hierarchical nature of mechanisms. Like the standard Bayesian net formalism, it models causal relationships using directed acyclic graphs. Given this appeal to acyclicity, causal cycles pose a prima facie problem for the RBN approach. This paper argues that the problem is a significant one given the ubiquity of causal cycles in mechanisms, but that the problem can be solved by combining two sorts of solution strategy in a judicious way.</p>},
	doi = {10.1007/s11229-013-0360-7},
	author = {Clarke, Brendan and Leuridan, Bert and Williamson, Jon}
}
@incollection {1223153,
	title = {The IARC and mechanistic evidence},
	booktitle = {Causality in the Sciences},
	year = {2011},
	pages = {91{\textendash}109},
	publisher = {Oxford University Press},
	abstract = {<p>The International Agency for Research on Cancer (IARC) is an organization which seeks to identify the causes of human cancer. For each agent, such as betel quid or Human Papillomaviruses, they review the available evidence deriving from epidemiological studies, animal experiments and information about mechanisms (and other data). The evidence of the different groups is combined such that an overall assessment of the carcinogenicity of the agent in question is obtained. In this paper, we critically review IARC{\textquoteright}s carcinogenicity evaluations. First we show that serious objections can be raised against their criteria and procedures - more specifically regarding the role of mechanistic knowledge in establishing causal claims. Our arguments are based on the problems of confounders, of the assessment of the temporal stability of carcinogenic relations, viz. How we should treat the carcinogenicity evaluations that were based on the current procedures. After showing that this question is important we argue that an overall dismissal of the current evaluations would be too radical. Instead, we argue in favour of a stepwise re-evaluation of the current findings.</p>},
	isbn = {9780199574131},
	author = {Leuridan, Bert and Weber, Erik},
	editor = {McKay Illari, Phyllis and Russo, Federica and Williamson, Jon}
}
@incollection {371044,
	title = {Conceptual tools for causal analysis in the social sciences.},
	booktitle = {Causality and probability in the sciences},
	year = {2007},
	pages = {197{\textendash}213},
	publisher = {College Publications},
	address = {London},
	isbn = {1904987354},
	author = {Weber, Erik},
	editor = {Russo, Federica and Williamson, Jon}
}
@incollection {373206,
	title = {Galton{\textquoteright}s blinding glasses: modern statistics hiding causal structure in early theories of inheritance.},
	booktitle = {Causality and probability in the sciences},
	year = {2007},
	pages = {243{\textendash}262},
	publisher = {College Publications},
	isbn = {1-904987-35-4},
	author = {Leuridan, Bert},
	editor = {Russo, Federica and Williamson, Jon}
}
