I am a Postdoctoral Researcher in Philosophy of Science at the John J. Reilly Center at the University of Notre Dame. I received my PhD from the Department of Philosophy, Logic and Scientific Method at the London School of Economics and Political Science. My primary interest is in scientific modelling. Specifically, I'm trying to work out in virtue of what they represent systems out there in the world. I think that to address this question it's worth listening to what other philosophers have to say about linguistic or pictorial representation. But I also believe that the question won't be answered fully unless we investigate how scientists use models in practice. I have a secondary interest in social choice theory and its applications beyond the aggregation of individual preferences.
(2016) On the Pragmatic Equivalence between Representing Data and Phenomena, Philosophy of Science, 83(2), pp. 171-191 Abstract
I investigate van Fraassen's claim that, for a given scientist, in a given context, there is no pragmatic difference between taking a model to accurately represent a target system (a physical system out there in the world) and a data model (a mathematical object extracted from that system).
I reconstruct van Fraassen's argument for this claim before demonstrating that it turns on the false premise that an act of representing that P commits the representer to the belief that P. So van Fraassen's claim that denying that models represent target systems would result in an instance of Moore's paradox fails. Unlike assertion, acts of representation fail to generate any doxastic commitments.
(This paper won me the Popper Prize for distinguished work by a graduate student in the philosophy department at the LSE.)
In this paper we explore the constraints that our preferred account of scientific representation places on the ontology of scientific models. Pace the Direct Representation view associated with Arnon Levy and Adam Toon we argue that scientific models should be thought of as fictional imagined systems, and clarify the relationship between imagination and representation.
(Forthcoming) Scientific Representation and Theoretical Equivalence, Philosophy of Science (PSA 2016 Proceedings) Abstract
In this paper I fruitfully connect two debates in the philosophy of science; the questions of scientific representation and model, and theoretical, equivalence. I argue that by paying attention to how a model is used to draw inferences about its target system, we can define a notion of theoretical equivalence that turns on whether their models licence the same inferences about the same target systems. I briefly consider the implications this has with respect to two questions that have recently been discussed in the context of the formal philosophy of science.
We provide a concise overview of the recent literature concerning scientific representation.
We provide an extensive overview of the recent literature concerning scientific representation.
(Forthcoming) Scientific Representation is Representation as (with Roman Frigg), in H-K Chao, J. Reiss and S-T Chen (eds.) Philosophy of Science in Practice: Nancy Cartwright and the Nature of Scientific Reasoning Abstract
Nelson Goodman distinguished between the notions of representation-of and representation-as. The former is bare denotation, akin to the relationship between a proper name and its bearer. The latter can be informative: the representation may be used to learn about the target. We propose a framework in which to understand how scientific representation is a specific case of representation-as.
(Forthcoming) Scientific Rationality by Degrees (with Alex Marcoci), in M. Massimi, J-W. Romeijn, and G. Schurz (eds.) Recent Developments in the Philosophy of Science - EPSA15 Dusseldorf, Springer Abstract
In a recent paper, Okasha imports Arrow's impossibility theorem into the context of theory choice. He shows that there is no function (satisfying certain desirable conditions) from profiles of preference rankings over competing theories, models or hypotheses provided by scientific virtues to a single all-things-considered ranking. This is a prima facie threat to the rationality of theory choice. In this paper we show this threat relies on an all-or-nothing understanding of scientific rationality and articulate instead a notion of rationality by degrees. The move from all-or-nothing rationality to rationality by degrees will allow us to argue that theory choice can be rational enough.
In the 2016 Fall semester I am teaching HPS 83801 - Philosophy of Science, a graduate survey course for the History and Philosophy of Science students at the University of Notre Dame. Course information can be found on Sakai.
During my time at LSE I was a teaching assistant for the following courses.
|PH101 Logic||PH101 Logic||PH101 Logic||PH101 Logic|
|PH201 Philosophy of Science||PH218 Philosophy of Biology|
I am comfortable teaching introduction to philosophy, philosophy of science, philosophy of language, history of analytic philosophy, and introductory logic and/or formal methods for philosophers.
In the academic year 2015-2016 I won the Teaching Prize for excellent class teaching from the Department of Philosophy, Logic and Scientific Method at the LSE (in the 2014-2015 academic year I was awarded an honourable commendation).
I think the question of scientific representation is genuinely interesting in and of itself. Scientific models are clearly about their targets. What establishes this? Does it work in the same way as mental, linguistic, pictorial, or cartographic representation? And in addition, most philosophers of science these days agree that models are important, if not the sole, representational units of science. But models aren't truth bearers in the same way that sentences or propositions are. So without an account of how models represent their targets, and how they do so accurately, I'm not sure we know what 'scientific realism' or 'scientific anti-realism' even mean any more.
This is a plaque affixed to the spaceship Pioneer 10. Well, it's a picture of a plaque affixed to the spaceship Pioneer 10. It was designed by Carl Sagan and, when interpreted appropriately, contains some very informative representational content about humans and the earth. For example, the geometric shape behind the human figures represents the Pioneer 10 itself. So the relative heights of the figures represent how tall we are. It is a nice example of how pictorial and scientific representation might be more alike than originally thought.
|"Scientific Representation and Theoretical Equivalence", PSA 2016, Atlanta, 3-5/11/16.|
|"Arrovian Consistency of Domains with a Fixed Preference", Central European Program in Economic Theory, Udine, 23-24/6/16.|
|"Models, Fictions, and Scientific Representation", Models and Explanations in Economics, Innsbruck, 10-12/6/16.|
|"From Hydraulic Machines to Immortal Rabbits", Models and Simulations 7, Barcelona, 18-16/5/16.|
|"Moving Beyond Arrow’s Theorem: Social Choice and Theory Choice", Choice Group, London, 4/5/16.|
|"Scientific Representation is Representation As", Modelling and Representation: How to Make World(s) with Symbols, San Sebastián, 10-12/12/15.|
|"On the Rationality of Theory Choice", Theory Choice meets Social Choice Symposium, EPSA 2015, Düsseldorf, 23-26/9/15.|
|"Ambiguity of Scientific Virtues in the Social Choice Framework", 8th Munich-Sydney-Tilburg Conference in Philosophy of Science, Tilburg, 10-12/6/15.|
Co-organiser of The Hole Shebang: New Perspectives on the Hole Argument. The workshop took place on 15 July 2016 at the LSE.
Co-organiser of Explanation, Normativity, and Uncertainty in Economic Modelling. The conference took place on 17-19 March 2016 at the LSE.
Co-organiser of the Theory Choice meets Social Choice Symposium at EPSA 2015. The symposium took place on 22-25 September 2015 in Düsseldorf.
Co-organiser of Decision, Games and Logic 2015. The workshop took place on 17-19 June 2015 at the LSE.
Co-organiser of the Fourth LSE Graduate Conference in Philosophy of Probability. The conference took place on 6-7 June 2014 at the LSE.