Epidemiological Method, Causal Inference, and Non-Randomized Statistics: The Case of Three Mile Island
Kristin Shrader-Frechetti
University of Notre Dame, Departments of Philosophy and Biological Sciences
Friday, 18 September 2009, 3:30 pm

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Abstract: This paper uses recent epidemiological studies of the Three Mile Island (TMI) nuclear accident to argue for 4 claims. These are (i) that the dominant scientific position on TMI health effects (that increased, TMI-area cancers probably have been caused by accident-related stress, not radiation) is arguably wrong; (ii) that an alternative scientific conclusion is more likely correct (radiation probably caused the increased health effects); (iii) that 2 methodological errors likely contributed to these TMI errors; and (iv) that avoiding these errors in future requires a fundamental shift in epidemiological method. The methodological errors, contributing to erroneous TMI conclusions, include misunderstanding the randomization conditions necessary for use of classical statistics -- and misunderstanding the constraints on causal inferences in observational, non-experimental studies. To avoid these errors in future, the paper argues that epidemiologists are likely to need fundamental changes in their methods, including much greater use of inference to the best explanation, especially contrastive explanation, and avoiding overemphasis on black-box, or risk-factor, epidemiology, to the exclusion of eco-epidemiology.

A Case for Scientific Pluralism
Hasok Chang
University College London, Department of Science and Technology Studies
Friday, 13 November 2009, 3:30 pm

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Abstract: I outline various arguments for normative scientific pluralism, by which I mean the doctrine that it is beneficial to have multiple systems of knowledge in each area of science.   I provide a different set of arguments for each of the various possible views about the aims of science.  If the main aim of science is taken to be Truth, the chief argument for pluralism is based on the unpredictability of scientific development: since we do not know which line of inquiry will be ultimately successful, it makes sense to cultivate various lines.  If the main aim of science is empirical adequacy or understanding, there are further arguments for pluralism because different systems of knowledge can contribute to the aim in different ways.  If we consider that science has various aims simultaneously, then there are even further pluralist arguments.  I close by indicating how history and philosophy of science can help put scientific pluralism into practice by assisting with the proliferation of systems of knowledge.

Science, Supposition and Reference:  The New Program
Robert Rynasiewicz
Johns Hopkins University , Department of Philosophy
Friday, 4 December 2009, 3:30 pm

Abstract: ‘Supposition’ is taken here in a strictly non-epistemic sense, as, e.g., in supposing for the sake of argument. Suppositions may involve what I call ‘objects of supposition’, i.e., entities whose existence is granted only courtesy of the supposition, e.g., a fictional character or object that exists only according to the story. Supposition and objects of supposition have a rich and characteristic linguistic phenomenology common to discourse about fictions, mathematical entities, and discarded hypothetical entities from the history of science. Indeed, barring magical theories of reference, all hypothetical entities in science should be regarded as objects of supposition. This raises a puzzle, viz., how is it possible to “discover” a hypothetically postulated entity.

After we resolve this apparent puzzle, we are left with a view of science that transcends the traditional realism-antirealism debates. The key distinction is not between the observable and the unobservable, but between the referring and the non-referring. This diachronically shifting distinction is necessarily cumulative and puts into new light both the traditional argument from instrumental success and the pessimistic meta-induction. There is also a corollary underwriting various applications of Ockam's razor.

Understanding, Formal Verification, and the Philosophy of Mathematics
Jeremy Avigad
Carnegie Mellon University , Department of Philosophy
Friday, 5 February 2010, 3:30 pm

Discovering Mechanisms in Cognitive Neurobiology:  An Experimentalist's Perspective
Edda Thiels
University of Pittsburgh , Department of Neurobiology
Friday, 26 February 2010, 3:30 pm

Getting Real about Genetics and Genomics: A Somewhat Antirealist Perspective
C. Kenneth Waters
University of Minnesota , Center for Philosophy of Science
Friday, 26 March 2010, 3:30 pm

(Real) Naturalism for Moral Philosophy: Sources, Difficulties, Solutions
Catherine Wilson
University of Aberdeen , Department of Philosophy
Friday, 9 April 2010, 3:30 pm

 

The Annual Lecture Series is hosted by the Center for Philosophy of Science.