Hesperus is Bosphorus

A group blog by philosophers in and from Turkey

Talk and Workshop at Bogazici, Samuel Fletcher (U. of Minnesota)

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Please join us for a talk and a two-part workshop at Bogazici University, both by Samuel Fletcher. Details below. All are welcome.

All events take place in TB 130 (Anderson Hall).

26 May 15:00-16:00 The Logic of Severe Testing I (Workshop)
26 May 17:00-19:00  “The Principle of Stability” (Colloquium)
27 May 16-18:00  The Logic of Severe Testing II (Workshop)
  • “The Principle of Stability” (Colloquium) How can inferences from idealized models to the phenomena they represent be justified when those models deliberately distort the phenomena? Pierre Duhem considered just this problem in part II, chapter III (“Mathematical Deduction and Physical Theory”) of The Aim and Structure of Physical Theory (1914), arguing that inferences and explanations from mathematical models of phenomena to real physical applications must also be demonstrated to be approximately correct when the (idealized) assumptions of the model are only approximately true. Despite being included in Duhem’s most influential contribution to philosophy of science, this chapter and the principle it contains is little discussed among philosophers. Yet mathematicians and physicists both contemporaneous with and subsequent to Duhem took up this challenge (if only sometimes implicitly), yielding a novel and rich mathematical theory of stability. My goals in this presentation are thus twofold: first, to trace some of the history of this principle of stability and its precursors in reference to their application in science, and second, to present a modern version of the principle, exploring some of its applications and implications, as well as comparing it to related notions that have received more attention.
  • The Logic of Severe Testing (Two-part Workshop) Deborah Mayo has for many years advocated for a modified version of classical Neyman-Pearson statistical testing as the correct account of inductive inference, most famously in her monograph Error and the Growth of Experimental Knowledge (Chicago, 1996).  While this approach uses probabilities, it does not assign them to hypotheses or propositions as Bayesians would.  Instead, testing procedures assign “fit” and “severity” scores to hypotheses or propositions based on observed data.  Those hypotheses or propositions passing a sufficiently high threshold for both receive justification for being fallibly inferred: they have been severely tested.  This work is an attempt to develop a general logical framework for Mayo’s account of severe testing that is a generalization from the specific examples she gives (usually z-tests).  The framework involves a two-dimensional many-valued logic–one dimension each for “fit” and “severity”–that is superintuitionistic: stronger than intuitionistic logic but weaker than classical logic.  This is a welcome result, since a particular hypothesis (e.g., “this chemical causes cancer”) not being severely tested should sometimes but not in general entail that its negation is severely tested.


If you have any questions, please contact mark.steen@boun.edu.tr

Written by markedwardsteen

May 19, 2016 at 3:31 pm

Posted in Uncategorized

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