Abstract
Mathematics plays a self-evidently important role in making scientific predictions. The rise of science as an epistemically superior mode of knowledge production over the past four centuries has depended on making accurate predictions; the apparent certainty of scientific knowledge has often been borne out by accurate predictions. Mathematics has been unarguably ‘effective’ in this sense. The question I want to explore here is how predictions have improved, that is how mathematics has become more effective, if effectiveness is measured in terms of producing accurate predictions.
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Notes
- 1.
It is worth noting that while Thayer used the École Polytechnique as a golden engineering credential, the École des ponts et chaussées and École du génie de mézières probably offered more relevant, if less elite, training.
- 2.
Dimensional analysis is a common enough engineering technique—it means making sure that the dimensions of a problem will cancel out to leave the answer in the desired units, whether pounds, kilos, inches, or newtons.
- 3.
Coulomb had introduced the calculus into statics in the 1770s. Military and civil engineering academies taught these methods in the period following the French Revolution.
- 4.
Here the British tradition of referring to “maths” makes this easier to explain than the American word “math.”
- 5.
This is a recent controversy in the United States.
- 6.
Here I highlight two epistemic virtues, but I do no mean to imply there were only two epistemic virtues in play in this tension.
- 7.
Limited, because they didn’t need to predict all possibilities. This wasn’t Hume’s problem of induction. They knew the bridge wasn’t going to lift off the ground spontaneously, turn into an apple, or vanish.
References
Akera, A. (2008). Calculating natural world: Scientists, engineers, and computers during the rise of U.S. cold war research. Cambridge: MIT Press.
Alder, K. (1997). Engineering the revolution: Arms and enlightenment in France, 1763–1815. Princeton: Princeton University Press.
Alder, K. (1999). French engineers become professionals; or, how meritocracy make knowledge objective. In W. Clark, J. Golinski, & S. Shaffer (Eds.), The sciences in enlightened Europe (pp. 94–125). Chicago: University of Chicago Press.
Brown, L. T. S. (1831). On the strength of pine and spruce timbers. Journal of the Franklin Institute 7(April), 238.
de Balzac, H. (1899). Scenes from country life: La Comédie Humaine (K. Wormeley, Trans.). Boston: Little Brown.
Galison, P., & Daston, L. (2007). Objectivity. New York: Zone Books.
Gilmour, C. S. (1971). Coulomb and the evolution of physics and engineering in eighteenth-century France. Princeton: Princeton University Press.
Graber, F. (2008). Purity and theory: Theoretical tools at the Ponts et Chaussées circa 1800. Technology and Culture, 49(4), 860–883.
Hacker, A. (2016). The math myth and other STEM delusions. New York: New Press.
Heyman, J. (1972). Coulomb’s Memoir on statics: An essay in the history of civil engineering Cambridge: Cambridge University Press.
Heyman, J. (1998). Structural analysis: A historical approach. Cambridge: Cambridge University Press.
Kranakis, E. (1997). Constructing a bridge: An exploration of engineering culture, design and research in nineteenth-century France and America. Cambridge: MIT Press.
Langins, J. (2004). Conserving the enlightenment: French military engineering from Vauban to the Revolution. Cambridge: MIT Press.
Narayayan, R. S., & Beeby, A. W. (2001). Introduction to design for civil engineers. London: Spon Press.
Phillips, C. J. (2014). New math: A political history. Chicago: University of Chicago Press.
Pickstone, J. (2000). Ways of knowing. Chicago: University of Chicago Press.
Picon, A. (1987–1988). Les ingénieurs et l’idéal analytique à la fin du XVIIIe siècle. Sciences et techniques en perspective 13, 70–108.
Sinclair, B. (1974). Philadelphia’s philosopher mechanics: A history of the Franklin Institute, 1824–1865. Baltimore: Johns Hopkins University Press.
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Johnson, A. (2017). Rational and Empirical Cultures of Prediction. In: Lenhard, J., Carrier, M. (eds) Mathematics as a Tool. Boston Studies in the Philosophy and History of Science, vol 327. Springer, Cham. https://doi.org/10.1007/978-3-319-54469-4_2
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