Sherri
Roush
Rice University, USA
Fall 2003
Tracking: Knowledge, Evidence, and Science
Sherri’s recent interests are the questions
of what knowledge is, what evidence is, and whether we should be
realists or anti-realists about scientific theories. A belief is
not knowledge merely in virtue of coinciding with the truth—that
could be accidental. It must coincide with the truth because it
is ‘following’ the truth. A fact is evidence for a hypothesis
when it is a discriminating indicator of that hypothesis, thus,
also when it provides a way of ‘following’ the hypothesis.
These are the intuitions behind the tracking accounts of knowledge
and evidence developed in her forthcoming book Tracking Truth: Knowledge,
Evidence, and Science. Considerations about evidence lead also to
a mixed realist-anti-realist view of scientific theories, according
to which we should be realists about low-level hypotheses, including
some about unobservable entities, and anti-realists about high-level
theories. Sherri is currently working on how to model surprisingness
of evidence, and also on what knowledge is and how it might have
evolved in the framework of evolutionary game theory. In her spare
time Sherri reads a lot of newspapers and watches big birds on the
Gulf Coast.
November 2010
University of California, Berkeley
Sherrilyn Roush is now Associate Professor of Philosophy, and faculty in the Group in Logic and the Methodology, at the University of California, Berkeley. She is the author of Tracking Truth: Knowledge, Evidence, and Science (Oxford, 2005), written partly during her stay at the Center, and more recently of "Randomized Controlled Trials and the Flow of Information," ‘‘Second- Guessing: A Self-Help Manual,’’ ‘‘Closure on Skepticism,’’ “Love Science,” ‘‘Optimism About the Pessimistic Induction,’ and “Fallibility and Authority in Science and Technology.” Her main current project is on fallibility, self-doubt, and justified belief, which has led to a second-order generalization of Bayesian rationality that shows how coherently to acknowledge and adjust for information about our unreliability. |
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