Learning Through Fictional Narratives in Art and Science

Chapter
Part of the Boston Studies in the Philosophy of Science book series (BSPS, volume 262)

Abstract

Thought experiments (henceforth, “TE’s”) in science take the form of short narratives in which various experimental procedures are described. The competent reader understands that these procedures have not been, and usually could not (for some appropriate modality) be, enacted. She is invited, however, to imagine or make believe that these procedures are enacted and to conclude that certain consequences would ensue, where this is taken to bear upon a more general question which is the topic of the TE. Perhaps the most famous example of such a device is Galileo’s “Tower” TE which aimed both to refute the standing Aristotelean account of the behavior of falling bodies, and to establish the alternative account favored by Galileo himself. The Aristotelean account held that the speed at which a body falls is directly proportional to its weight. Galileo asks us to imagine that we take two bodies, one heavy [H] and one light [L], to the top of a high tower. We strap the bodies together and drop the resulting object [H+L] from the tower. The Aristotelean is then committed to two contradictory claims. First, since [H+L] is heavier than [H], it should fall faster than H. On the other hand, since [L] falls more slowly than [H] it should retard the fall of [H], and since [H] falls more quickly than [L] it should accelerate the fall of [L]. So [H+L] should fall at a speed somewhere between the rate of fall of [H] and the rate of fall of [L]. Since the Aristotelean view leads to an absurdity—that [H+L] will fall both more quickly and more slowly than [H]-rate of fall must be independent of weight. Given this “intermediate” conclusion, Galileo further concludes that (if we remove the resistance of a medium) all bodies fall at the same rate.1

Keywords

Cognitive Resource Literary Work Propositional Theory Fidelity Constraint Fictional Narrative 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

Earlier versions of this paper were presented at the London School of Economics/Courtauld Institute of Art conference, “Beyond Mimesis and Nominalism: Representation in Art and Science” in June 2006, at a workshop on “Thought Experiments” held at the University of Toronto in May 2007, and at a colloquium at London School of Economics in December 2007. I am grateful to all those who offered helpful comments and criticisms on those occasions. I am also grateful to students in the graduate pro-seminar on “Thought Experiments” that I co-taught at McGill in Fall 2006 for their feedback on some of the ideas in this paper. I am especially grateful to the editors of this volume, and to two anonymous referees, for critical comments and suggestions on an earlier draft of this paper, which helped me to clarify and refocus the paper in ways that (I hope) considerably improved it. Finally, I wish to thank the Social Sciences and Humanities Research Council of Canada, a research grant from whom facilitated the research for this paper.

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© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.McGill UniversityMontrealCanada

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