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Toy Statistical Models and Legal Reasoning
A great deal of theorising about the proper place of statistical reasoning in the courtroom revolves around several canonical thought experiments that invoke toy statistical models of an idealised situation. I will argue that these canonical thought experiments are flawed in various (albeit interesting) ways. In some cases, the flaws involve subtle underspecification that leads to ambiguity about the intuitive judgement; in other cases, the flaw is that the thought experiment stipulates that we forgo freely-available and relevant evidence. The common thread is that uncertainty about the statistical model itself is left unaccounted for. The upshot is that these thought experiments do not succeed in undermining the use of statistical evidence in the courtroom.
Prof. Mark Colyvan is professor of philosophy at the University of Sydney (Australia) and a visiting professor at the Munich Center for Mathematical Philosophy, Ludwig-Maximilians University in Munich (Germany). He holds a BSc(Hons) in mathematics (University of New England) and a PhD in philosophy (Australian National University). He is a former president of the Australasian Association of Philosophy and a former president of the Society for Risk Analysis (Australia and New Zealand). He mainly works on logic, decision theory, philosophy of mathematics, environmental philosophy, conservation biology, and ecology. He has written numerous articles on these and other topics, along with the books The Indispensability of Mathematics (Oxford University Press, 2001), Ecological Orbits: How Planets Move and Populations Grow (with Lev Ginzburg, Oxford University Press, 2004), and An Introduction to the Philosophy of Mathematics (Cambridge University Press, 2012).