Grading Evidence of Mechanisms

Conference: Grading Evidence of Mechanisms


Date: 4-5 September


Location: University of Kent


Science is largely involved with discovering mechanisms. While protocols have been developed for grading evidence of statistical dependencies as a means to establish causal claims in medicine and public health, not as much has been said about how to grade evidence of mechanisms on the path to mechanism discovery – this task is typically left to the intuition of individual researchers. Also, while the role of mechanistic research strategies has been widely studied regarding molecular life sciences, and to some extent social sciences and psychology, not as much has been said about the role of mechanisms in the physical sciences. This conference will explore issues related to the role of mechanisms, and the quality of evidence of mechanisms in the sciences.




Monday 4/9

09:45 Welcome + coffee/tea

10:00 – 11:30 Keynote, Tudor Baetu: Comparability, randomization and causal Inference

11:30 – 11:45 Break

11:45 – 12:30 Luana Poliseli: Explaining ecological phenomena by means of mechanistic models – is it possible?

12:30 – 13:15 Yin Au: Hierarchical use of visual evidence in cell biological mechanism research

13:15 – 14:45 Lunch

14:45 – 15:30 Michael Wilde: Evidential pluralism and hazard identification

15:30 – 16:15 Beth Shaw: Grading evidence of mechanisms – how is evidence of mechanisms being graded in practice?

16:15 – 16:30 Break

16:30 – 18:00 Keynote, Meinard Kuhlmann: Identifying mechanisms in complex systems


Tuesday 5/9

09:45 – 11:15 Keynote, Emma Tobin: Mechanisms and natural kinds

11:15 – 11:30 Break

11:30 – 12:15 Thomas Lodewyckx: Grading evidence for mechanisms in biological research

12:15 – 13:00 Brendan Clarke, Phyllis Illari & Federica Russo: Datified evidence of mechanisms

13:00 – 14:30 Lunch

14:30 – 15:45 Book Symposium: Routledge Handbook on Mechanisms and Mechanical Philosophy

15:45 – 16:00 Break

16:00 – 17:30 Keynote, Erik Weber: Mechanistic evidence and the asymmetry of causation

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