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Science as (Historical) Narrative

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Abstract

The traditional mode of explanation in physics via deduction from partial differential equations is contrasted here with explanation via simulations. I argue that the different technologies employed constitute different languages, which support different sorts of narratives. The narratives that accompany simulations and articulate their meaning are typically historical or natural historical in kind. They explain complex phenomena by growing them rather than by referring them to general laws. Examples of such growth simulations and growth narratives come from the evolution of wave functions in quantum chaos, snowflake formation, and Etruscan genetics. The examples suggest a few concluding remarks on historical explanation.

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Notes

  1. In reflecting on the relation of technologies to narratives I am inspired directly by the recent works of Mary Morgan on the way narrative functions in the use of models by economists (Morgan 2001, 2007). More generally, I have long followed the works of Hans-Jörg Rheinberger, for example, his thoughts on Historiality, Narration, and Reflection (1997, ch. 11): “Experimental systems contain remnants of older narratives as well as shreds and traces of narratives that have not yet been related” (p. 186). They are “generators of epistemic novelty” (p. 229). Other relevant sources, on narrative structure in evolution, primatology, and mathematics, are (Beer 1983; Haraway 1989; Alexander 2002), although they are primarily concerned with how structures of scientific understanding express broader cultural narratives.

  2. Although Berman wants to employ his views on language as a defense against postmodern historicist relativism, much of his discussion does not depend on that perspective. A key source, and foil, for Berman is (Ong 1982).

  3. For an account of the historical significance of this move from microscopic to macroscopic analysis for British physics, see (Smith and Wise 1989, pp. 149–168). It was critically important for such diverse areas as electrostatics (Green), the wave theory of light (MacCullagh), elastic solids (Stokes), and electromagnetic theory (Maxwell).

  4. Fourier’s own rationale for this procedure was by no means standard. Poisson (1835) devoted an entire book to challenging its validity.

  5. Courant and Hilbert (1953, pp. 69–73). For physical applications, they refer the reader to “elementary texts” (p. 4, n.1). The convergence proof for piecewise continuous functions was given by Dirichlet in 1829 (1889) and (1837).

  6. Discussion and references in (Smith and Wise 1989, pp. 192–194). Thomson may not yet have been familiar with Dirichlet’s work on convergence.

  7. In “Prisoner’s Dilemma,” Morgan (2007) illuminates how the apparently poverty-stricken 2 × 2 matrix for the famous dilemma acquires a rich and varied set of meanings through the stories with which economists surround and interpret it.

  8. Laughlin and Pines (2000) cite this situation and give a polemical critique of deductive and reductive quantum mechanics in their manifesto for the twenty-first century, arguing that a fundamentally different approach is required to deal with the complex systems of everyday life and their emergent properties. They call this new physics the study of “complex adaptive matter” (p. 30). They and their collaborators extend the analysis to mesoscopic systems, including bio-molecular systems, in (Laughlin et al. 2000).

  9. Heller and Tomsovic (1993). On the place of this work within trends in the physics of complexity see Wise and Brock (1998).

  10. Biologists will insist that the process is not properly called evolution but only development. No doubt they are correct, but I will maintain the authors’ broader usage here and below as an indication of their biological orientation.

  11. Lorraine Daston has recently made me aware of an earlier exception (Hellmann et al. 1893). See Daston et al. (2007, pp. 148–155).

  12. Even the Big Bang theory and evolution of the cosmos appear not to have turned elementary particles into historical objects, presumably because they are not known by evolutionary means.

  13. A better analogy might be the growth of many different kinds of tissues from a single kind of stem cell. Laughlin et al. (2000) also invoke “evolution” (p. 35)—along with growth (p. 32), aging (pp. 32, 34), and adaptation (as in complex adaptive matter, or behavior, p. 36)—to capture the analogy of physical to biological processes. Indeed they offer the hint that the phenomenon of protection (independence of a mesoscopic physical system from small changes in microscopic structure or laws) may in biology “arise from the necessity of tolerating diversity.”

  14. Explanations of this kind are not so surprising for simulations in field sciences like geology, but the point is the same: simulations often explain by supporting natural histories and their narratives (Oreskes 2007).

  15. Hempel’s brief discussions of “historic-genetic” or simply “genetic” explanation (Hempel 1965b, pp. 447–453; Hempel 2001, pp. 287–289), by which he referred to an account of an event by tracing its origins, or genesis, might seem promising for narratives and simulations, but Hempel quickly reduced any valid genetic explanation to a sequence of stages connected by nomological explanation, perhaps combined with description.

  16. This despite Danto’s explicit belief that he represented the historicizing “revolution” initiated by Thomas Kuhn and Norman Hanson against the Hempelian view of science (Danto 1985, p. xi). The revolution, however, did not stress science as narrative, nor did it attack deduction as explanation. It did insist that observation is always theory-dominated and subject to interpretation, which can be seen as introducing a narrative thrust, especially in history of science.

  17. See, however, Ricoeur’s brief reference to explanations in “cosmology, geology, and biology” and certain parts of history as explanations in which retrodiction is at work to establish necessary conditions for something to have happened but prediction based on sufficient conditions is not possible (Ricoeur 1984, 135).

  18. I leave out of account the belief of the Annales school that social history, because quantitative and employing mathematical models, is scientific rather than narrative, which is precisely the dichotomy I am rejecting.

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Acknowledgments

For extensive discussions I thank Mary Morgan, Lorraine Daston, and my long-time collaborator and muse Elaine Wise, also Guido Barbujani, Krishna Veeramah, Philip Kitcher, Manfred Laubichler, and an especially probing anonymous referee. An earlier version benefited from comments of participants in the conference on Historical Epistemology at the Max Planck Institute for History of Science, 24–26 July 2008.

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Correspondence to M. Norton Wise.

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Delivered originally as the History of Science Society Distinguished Lecture, 20 November 2009, Phoenix, Arizona.

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Wise, M.N. Science as (Historical) Narrative. Erkenn 75, 349–376 (2011). https://doi.org/10.1007/s10670-011-9339-2

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