Resume

• 2009

  Doctor of Philosophy - PhD

  History and Philosophy of Science and Technology

  University of Toronto

• 2000

  Bachelor of Arts

  Philosophy

  University of Toronto

• Qualitative Research

  Research

  Critical Thinking

  Research Design

  Technical Writing

  Editing

  Scientific Writing

  Lecturing

  Science

  Student Affairs

  Public Speaking

  Philosophy Of Science

  University Teaching

  Data Analysis

  Microsoft Office

  Academic Writing

  Teaching

  Higher Education

  The Generality of Scientific Models: A Measure-Theoretic Approach

  What is it for a scientific theory or model to be \"general?\" Can one model be more or less general than another? And how could we tell? In this paper we attempt to answer these questions using a branch of mathematics called measure theory.\n\nScientific models are often said to be more or less general depending on 'how many' cases they cover

  but making this intuitive notion precise has been challenging. In this paper we argue that one prominent notion of generality

  the cardinality approach

  will not work

  and we present a novel account based on measure theory. Our account solves several problems

  and also gives insight into assessments of generality. To illustrate our view

  we apply the measure-theoretic account to an example from Structural Genomics

  a field of study focussed on building three-dimensional models of large biological molecules like proteins.

  The Generality of Scientific Models: A Measure-Theoretic Approach

  The domain relativity of evolutionary contingency

  A key issue in the philosophy of biology is evolutionary contingency

  the degree to which evolutionary outcomes could have been different. Contingency is typically contrasted with evolutionary convergence

  where different evolutionary pathways result in the same or similar outcomes. Convergences are given as evidence against the hypothesis that evolutionary outcomes are highly contingent. But the best available treatments of contingency do not

  when read closely

  produce the desired contrast with convergence. Rather

  they produce a picture in which any degree of contingency is compatible with any degree of convergence. This is because convergence is the repeated production of a given outcome from different starting points

  and contingency has been defined without reference to the size of the space of possible outcomes. In small spaces of possibilities

  the production of repeated outcomes is almost assured. This paper presents a definition of contingency which includes this modal dimension in a way that does not reduce it to the binary notion of contingency found in standard modal logic. The result is a conception of contingency which properly contrasts with convergence

  given some domain of possibilities and a measure defined over it. We should therefore not ask whether evolution is contingent or convergent simpliciter

  but rather about the degree to which it is contingent or convergent in various domains

  as measured in various ways.

  The domain relativity of evolutionary contingency

  PhD in Philosophy of Science

  teaching at Trent University.

  Cory

  Lewis

  Trent University

  University of Toronto

  Institute for the History and Philosophy of Science and Technology

  University of Toronto

  Trent University

  Lecturer

  University of Toronto

  PhD Candidate

  Institute for the History and Philosophy of Science and Technology

  University of Toronto