October 2015 Lunchtime Abstracts & Details

::: Attribution, Prediction, and the Causal Interpretation Problem in Epidemiology
Alex Broadbent
University of Johannesburg, Dept. of Philosophy
Tuesday, October 6, 2015
12:05 pm, 817R Cathedral of Learning

Abstract: In contemporary epidemiology, there is a movement, part theoretical and part pedagogical, attempting to discipline and clarify causal thinking. I refer to this movement as the Potential Outcomes Approach (POA). It draws inspiration from the work of Donald Ruben and, more recently, Judea Pearl, among others. It is most easily recognized by its use of Directed Acyclic Graphs (DAGs) to describe causal situations, but DAGs are not the conceptual basis of the POA in epidemiology. The conceptual basis (as I have argued elsewhere) is a commitment to the view that the hallmark of a meaningful causal claim is that they can be used to make predictions about hypothetical scenarios. Elsewhere I have argued that this commitment is problematic (notwithstanding the clear connections with counterfactual, contrastive and interventionist views in philosophy). In this paper I take a more constructive approach, seeking to address the problem that troubles advocates of the POA. This is the causal interpretation problem (CIP). We can calculate various quantities that are supposed to be measures of causal strength, but it is not always clear how to interpret these quantities. Measures of attributability are most troublesome here, and these are the measures on which POA advocates focus. What does it mean, they ask, to say that a certain fraction of population risk of mortality is attributable to obesity? The pre-POA textbook answer is that, if obesity were reduced, mortality would be correspondingly lower. But this is not obviously true, because there are methods for reducing obesity (smoking, cholera infection) which will not reduce mortality. In general, say the POA advocates, a measure of attributability tells us next to nothing about the likely effect of any proposed public health intervention, rendering these measures useless, and so, for epidemiological purposes, meaningless. In this paper I ask whether there is a way to address and resolve the causal interpretation problem without resorting to the extreme view that a meaningful causal claim must always support predictions in hypothetical scenarios. I also seek connections with the notorious debates about heritability.

::: On Stuff
James Weatherall, Visiting Fellow
University of California, Irvine
Dept. of Logic and Philosophy of Science
Tuesday, October 13, 2015
12:05 pm, 817R Cathedral of Learning

Abstract: Discussions of physical "ontology" often come down to two basic options. Either the basic physical entities are particles, or else they are fields. (A third option, not for the faint of heart, is to accept some combination of the two.) I will argue that, in fact, it is not at all clear what it would mean to say that the world consists of fields. Speaking classically (i.e., non-quantum-ly), there are many different sorts of thing that go by the name "field", each with different representational roles. Even among those that have some claim to being "fundamental" in the appropriate sense, it does not seem that a single interpretational strategy could apply in all cases. I will end by suggesting that standard strategies for constructing quantum theories of fields are not sufficiently sensitive to the different roles that "fields" can play in classical physics. Along the way, I will say something about an old debate in the foundations of relativity theory, concerning whether the spacetime metric is a "geometrical" or "physical" field. The view I will defend is that the metric is much like the electromagnetic field: geometrical!

::: Managing Complexity: Challenges of Modeling in Integrative Systems Biology
Nancy J. Nersessian, Senior Visiting Fellow
Harvard University, Dept. of Psychology
Friday, October 16, 2015
12:05 pm, 817R Cathedral of Learning

Abstract: Over the last 10 years there has been a rapid growth in analyses of computational modeling and simulation in the philosophy of science. A salient aspect of computational simulation, and the one which has attracted the most substantial philosophical interest so far, is its ability to extend the power and reach of theories in modern science beyond what could be achieved by pencil and paper alone. Work on simulations has largely concentrated on simulations built using established background theories or theoretical models and the relations between these simulations and theory. Examples have been sourced mainly from the physical sciences, including astrophysics, fluid dynamics, nanophysics, climate science and meteorology. My research group’s 4-year ethnographic investigations of modeling practices in integrative systems biology have revealed that not all equation-based modeling is theory-driven. The modelers we have studied have no background body of laws and principles of the biological domain, which could then provide the resources for constructing models, such as specifying which representations to use that will reliably lead to a good representation in various data situations. In integrative systems biology, engineers and applied mathematicians with little biological knowledge and usually no experimental experience attempt to model complex nonlinear biological networks for which the data are often sparse and are rarely adequate for applying a set mathematical framework. This situation forces researchers to develop innovative methodological strategies tailored to the problem, a practice we characterize as adaptive problem solving.

Models are strategic adaptations to a complex set of constraints system biologists are working under, ranging from data constraints to cognitive constraints to collaboration constraints. They build models by piecing together bits of biological information and data, and use mathematical and computational techniques to create stable models. These processes transform not only the shape of the solutions, but also the problems, as researchers figure out what actual problem can be solved with the data at hand. Simulation plays a central exploratory role. We argue that simulation in systems biology is not, as currently characterized, just for experimenting on systems in order to find out the consequences of a model, but plays a fundamental role in incrementally building the model, enabling the modeler to learn the relevant known and unknown features of a system and to gain an understanding of and make inferences about its dynamics. Simulation’s roles as a cognitive resource make possible the construction of representations of complex systems without a theoretical basis. Through the building process modeler and model become a coupled cognitive system, which enables a modeler with limited knowledge of biology to make fundamental biological discoveries, as we have witnessed.

::: Reasoning from Regularities: Science and Cognitive Science
Matthias Unterhuber, Visiting Fellow
University of Bern, Dept. of Philosophy
Tuesday, October 27, 2015
12:05 pm, 817R Cathedral of Learning
CANCELED

Abstract: One aim of the scientific endeavor is the inquiry into the laws of our universe. In light of this, it is surprising that Bayesianism is advocated as one of the best current models of scientific inquiry since—as I shall argue—standard Bayesian accounts are ill-equipped to describe regularities let alone reasoning with regularities with exceptions. Two problems are identified. Firstly, a purely subjective account of Bayesianism is severely limited in which kind of exception structures it can describe. Secondly, it is still more puzzling how such an account could deal with the largely overlooked yet important class of regularities such as ‘mosquitoes carry Malaria’; these regularities do not require the majority of individuals to fall under the predicated property. For example, ‘mosquitoes carry Malaria’ seem perfectly fine to assert, in spite of only a minority of mosquitoes carrying Malaria. In fact, it is not Bayesianism alone that is challenged by the second problem but rather probabilistic accounts of scientific inquiry in general.

::: Continuities and Discontinuities across Theory Change in Cassirer’s Relativized Conception of the A Priori
Francesca Biagioli, Visiting Fellow
University of Konstanz, Dept. of Philosophy
Friday, October 30, 2015
12:05 pm, 817R Cathedral of Learning

Abstract: Ernst Cassirer is usually acknowledged as one of the forerunners of a relativized conception of the a priori. However, Michael Friedman – who is one of the main proponents of such a conception in contemporary philosophy of science – draws back the idea of a relativized a priori to Hans Reichenbach’s (1920) distinction between two meanings of the notion of a priori in Kant’s philosophy: the first is that a priori principles are valid for all time; the second is that these principles are constitutive of experience, insofar as they provide nonempirical presuppositions for the definition of empirical objects. This distinction suggests that, although the first meaning of the notion of a priori was disproved by Einstein’s general relativity, the second meaning applies to Einstein’s principle of equivalence as a coordinating principle linking Riemannian geometry to empirical reality.
Even though Friedman attaches particular importance to Cassirer’s idea of a renewal of Kant’s transcendental philosophy in its connection with the history of science, his objection is that Cassirer did not take into account discontinuities in the formulation of the coordinating principles. My suggestion is that Cassirer’s contrast with Reichenbach rather depends on the fact that Cassirer – while emphasizing that classical mechanics and general relativity presuppose completely different geometrical hypotheses – argued for continuity in the formation of mathematical and empirical concepts. In doing so, he formulated an argument that is not restricted to a retrospective view of continuity in terms of inclusion of the mathematical structures of the former theories in that of the new theory. Cassirer’s goal was to show that even the new formulation of natural laws had been foreshadowed in the form of mathematical hypotheses.