2000 HSS/PSA Program 1 - History of Science Society

Ronald␣ N. Giere University of Minnesota
PSA Abstracts
The Perspectival Nature of Scientific Observation
Scientific observation, I claim, is perspectival. My paradigm for perspectivism
is human color vision. Rejecting both claims that colors are objective and claims
that they are subjective, I argue that colors are perspectival. They are part of the
perspective from which humans view the world. Using examples from astronomy,
I then point out that scientific observation is perspectival in roughly the same
way as human color vision. Although perspectivism is often dismissed as just
another form of relativism, I argue that it is a form of realism, and that this is a
perfectly reasonable conclusion from fairly obvious scientific facts.
James Guszcza Allstate Research and Planning
On the Information Theoretic Approach to Statistical Mechanics
The dual issues of the role of ergodic theory in statistical mechanics and the
status of Gibbs’ canonical ensemble have long been controversial issues in the
philosophy of physics. It is well known that E. T. Jaynes outlined a theory of
classical, equilibrium statistical mechanics in which ergodic theory plays no
role. Jaynes “derives” the canonical ensemble using a principle of inductive
inference known as the Principle of Maximum Entropy [PME]. PME is
controversial in its own right, but Jaynes’ theory of statistical mechanics faces
an even bigger problem: in order to apply PME to the case of statistical mechanics,
Jaynes must assume a uniform “prior probability” measure on phase space. This
paper does not dwell on the controversies surrounding the PME. However, a
concrete justification of the uniform “prior” measure is suggested. Namely, it is
pointed out that the uniform measure is implicitly defined by the symplectic
structure of the phase space of a classical system. Besides filling the most serious
conceptual gap in Jaynes’ theory, this result clarifies a point at which Jaynes’
theory makes contact with the underlying physics.
P
S
A
Daniel␣ M. Hausman University of Wisconsin
Causal Relations Among Tokens, Types, and Variables
There are causal relations between token events, between properties or event
types, between variables, and between values of variables. This essay explores
what these varieties of causal relation have to do with one another. It presents
and criticizes Ellery Eells’ view that type-level and token-level causation are
independent, and it endorses parts of Daniel Hausman’s view that type-level
causal claims are modal generalizations of token-level claims. It defends the
219