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International Studies in The Philosophy of Science | 2011

Mechanistic Evidence: Disambiguating the Russo–Williamson Thesis

Phyllis McKay Illari

Russo and Williamson claim that establishing causal claims requires mechanistic and difference-making evidence. In this article, I will argue that Russo and Williamsons formulation of their thesis is multiply ambiguous. I will make three distinctions: mechanistic evidence as type vs object of evidence; what mechanism or mechanisms we want evidence of; and how much evidence of a mechanism we require. I will feed these more precise meanings back into the Russo–Williamson thesis and argue that it is both true and false: two weaker versions of the thesis are worth supporting, while the stronger versions are not. Further, my distinctions are of wider concern because they allow us to make more precise claims about what kinds of evidence are required in particular cases.


Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences | 2010

Function and Organization : Comparing the mechanisms of protein synthesis and natural selection

Phyllis McKay Illari; Jon Williamson

In this paper, we compare the mechanisms of protein synthesis and natural selection. We identify three core elements of mechanistic explanation: functional individuation, hierarchical nestedness or decomposition, and organization. These are now well understood elements of mechanistic explanation in fields such as protein synthesis, and widely accepted in the mechanisms literature. But Skipper and Millstein have argued (2005) that natural selection is neither decomposable nor organized. This would mean that much of the current mechanisms literature does not apply to the mechanism of natural selection. We take each element of mechanistic explanation in turn. Having appreciated the importance of functional individuation, we show how decomposition and organization should be better understood in these terms. We thereby show that mechanistic explanation by protein synthesis and natural selection are more closely analogous than they appear--both possess all three of these core elements of a mechanism widely recognized in the mechanisms literature.


Archive | 2018

Evaluating Evidence of Mechanisms in Medicine: Principles and Procedures

Veli-Pekka Parkkinen; Christian Wallmann; Michael Wilde; Brendan Clarke; Phyllis McKay Illari; Michael P. Kelly; Charles Norell; Federica Russo; Beth Shaw; Jon Williamson

This book is the first to develop explicit methods for evaluating evidence of mechanisms in the field of medicine. It explains why it can be important to make this evidence explicit, and describes how to take such evidence into account in the evidence appraisal process. In addition, it develops procedures for seeking evidence of mechanisms, for evaluating evidence of mechanisms, and for combining this evaluation with evidence of association in order to yield an overall assessment of effectiveness. n nEvidence-based medicine seeks to achieve improved health outcomes by making evidence explicit and by developing explicit methods for evaluating it. To date, evidence-based medicine has largely focused on evidence of association produced by clinical studies. As such, it has tended to overlook evidence of pathophysiological mechanisms and evidence of the mechanisms of action of interventions. n nThe book offers a useful guide for all those whose work involves evaluating evidence in the health sciences, including those who need to determine the effectiveness of health interventions and those who need to ascertain the effects of environmental exposures.


Illari, P.M. & Russo, F. & Williamson, J. (Eds.). (2011). Causality in the sciences. New York: Oxford University Press | 2011

Causality in the Sciences

Phyllis McKay Illari; Federica Russo; Jon Williamson


European journal for philosophy of science | 2012

What is a mechanism? Thinking about mechanisms across the sciences

Phyllis McKay Illari; Jon Williamson


Archive | 2014

Causality: Philosophical Theory meets Scientific Practice

Phyllis McKay Illari; Federica Russo


Theoria-revista De Teoria Historia Y Fundamentos De La Ciencia | 2011

Models for prediction, explanation and control: Recursive Bayesian networks

Lorenzo Casini; Phyllis McKay Illari; Federica Russo; Jon Williamson


In: Illari, PM and Russo, F and Williamson, J, (eds.) Causality in the sciences. (818 - 844). Oxford University Press: Oxford. (2011) | 2011

Mechanisms are Real and Local

Phyllis McKay Illari; Jon Williamson


Archive | 2011

Models for Prediction, Explanation and Control

Lorenzo Casini; Phyllis McKay Illari; Federica Russo; Jon Williamson


Philosophy & Technology | 2011

Why theories of causality need production : an information-transmission account

Phyllis McKay Illari

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Brendan Clarke

University College London

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