Abstract
The measurements scientists make and the data that they produce from them generally constitute the basis of scientific claims. Here I investigate how natural scientists make decisions about the inclusion/exclusion of certain measurements in/from their data sources. I first show that there is a radical uncertainty in the discovery sciences, whereby they need to be certain that there is a natural object present that exhibits itself in a data (graph), and they need to be certain about the data (graph) to know whether there is any phenomenon. Moreover, scientists exclude measurements from their data sources even before attempting to mathematize and interpret the data. The excluded measurements therefore do not even enter the ground from and against which the scientific phenomenon emerges and therefore remain invisible to it. I conclude by encouraging science educators to squarely address this aspect of the discovery sciences in their teaching, which has both methodological and ethical implications.
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Notes
- 1.
Technically, any function f(x) can be expressed by means of a Fourier series. A Fourier expansion of a function f(x) is given by
$$ f(x)=\frac{1}{2}{a}_0+{\displaystyle \sum_{n=1}^{\infty }{a}_n \cos (nx)+}{\displaystyle \sum_{n=1}^{\infty }{b}_n \sin (nx)}, $$where the coefficients can be found by
$$ {a}_0=\frac{1}{\pi}{\displaystyle {\int}_{-\pi}^{\pi} f(x) dx;}\kern0.5em {a}_n=\frac{1}{\pi}{\displaystyle {\int}_{-\pi}^{\pi} f(x) \cos (nx) dx;}\kern0.5em {b}_n=\frac{1}{\pi}{\displaystyle {\int}_{-\pi}^{\pi} f(x) \sin (nx) dx}. $$Once such an expansion has been found, scientists eliminate the higher frequencies, for example, by setting all an = 0 and bn = 0 for n > 5 or n > 7, whichever leads to a “nice” curve when the Fourier expansion is reversed.
- 2.
In the natural sciences, implicitly or explicitly, some recorded signal h(x) is taken to be the result of a convolution of the true signal f(x) from the phenomenon and the instrument function g(x). The three functions are related according to
$$ h(x)={\displaystyle {\int}_{-\infty}^{+\infty } f(t) g\left( x- t\right) dt}. $$When scientists know the instrument function g(x), then they can obtain f(x) by means of process called deconvolution . But even if they do not have g(x), they tend to eliminate the influence of their instrumentation by developing better equipment.
- 3.
Minimal essential medium (MEM) is a cell culture solution containing amino acids, vitamins, minerals (inorganic salts), nutrients (energy source), and various other components.
- 4.
The uncertainty principle states that the product of the uncertainty of complementary variables such as position x and momentum p always is greater or equal to some constant: Δx · Δp ≥ ħ/2, where ħ is the reduced Planck’s constant.
- 5.
Atlantic salmon is from the genus Salmo, whereas Pacific salmon is from the genus Oncorhynchus. There are actually six species from this genus in the Pacific Northwest, five bearing the common name salmon (chinook [O. tsawytscha], chum [O. keta], coho [O. kisutch], pink [O. gorbuscha], and sockey [O. nerka]) and one with the common name rainbow trout (steelhead [O. mykiss]).
- 6.
Disciplinary vision is a dialectical phenomenon: it is required to seeing certain phenomena and, in so doing, no longer sees (other) phenomena. Foucault (1975) articulated the general relation between discipline (imposition of force) and discipline (form of knowledge), and my own research showed the process in operation in the becoming of ecologists (Roth and Bowen 2001).
References
Alexander, G., Sweeting, R., & McKeown, B. (1994). The shift in visual pigment dominance in the retinae of juvenile coho salmon (Oncorhynchus kisutch): An indicator of smolt status. Journal of Experimental Biology, 195, 185–197.
Bijker, W. E., Hughes, T. O., & Pinch, T. (Eds.). (2012). The social construction of technological systems: New directions in the sociology and history of technology. Cambridge, MA: MIT Press.
Cobb, P., & Tzou, C. (2009). Supporting students’ learning about data generation. In W.-M. Roth (Ed.), Mathematical representation at the interface of body and culture (pp. 135–170). Charlotte: Information Age Publishing.
Collins, H. M. (2001). Tacit knowledge, trust and the Q of Sapphire. Social Studies of Science, 31, 71–85.
Couzin-Frankel, J. (2013). The power of negative thinking. Science, 342, 68–69.
Dose, V. (2004). Data analysis via Bayesian probability theory. http://www.mpg.de/841061/forschungsSchwerpunkt. Accessed 1 Dec 2013.
Foucault, M. (1975). Surveiller et punir: Naissance de la prison [Discipline and punish: Birth of the prison]. Paris: Gallimard.
Garfinkel, H. (2002). Ethnomethodology’s program: Working out Durkheim’s aphorism. Lanham: Rowman & Littlefield.
Garfinkel, H., Lynch, M., & Livingston, E. (1981). The work of a discovering science construed with materials from the optically discovered pulsar. Philosophy of the Social Sciences, 11, 131–158.
Gooding, D. (1992). Putting agency back into experiment. In A. Pickering (Ed.), Science as practice and culture (pp. 65–112). Chicago: University of Chicago Press.
Govardovskii, V. I., Fyhrquist, N., Reuter, T., Kuzmin, D. G., & Donner, K. (2000). In search of the visual pigment template. Visual Neuroscience, 17, 509–528.
Hárosi, F. I. (1987). Cynomolgus and Rhesus monkey visual pigment: Application of Fourier transform smoothing and statistical techniques to the determination of spectral parameters. Journal of General Physiology, 89, 717–743.
Henry, M. (2000). Incarnation: Une philosophie de la chair [Incarnation: A philosophy of the flesh]. Paris: Éditions du Seuil.
Latour, B. (1987). Science in action: How to follow scientists and engineers through society. Cambridge, MA: Harvard University Press.
Lave, J. (1988). Cognition in practice: Mind, mathematics and culture in everyday life. Cambridge: Cambridge University Press.
Lynch, M. (1985). Art and artifact in laboratory science: A study of shop work and shop talk in a laboratory. London: Routledge & Kegan Paul.
Lynch, M. (1990). The externalized retina: Selection and mathematization in the visual documentation of objects in the life sciences. In M. Lynch & S. Woolgar (Eds.), Representation in scientific practice (pp. 153–186). Cambridge, MA: MIT Press.
Medical Billing and Coding. (2010). Sitting is killing you. http://lifehacker.com/5800720/the-sitting-is-killing-you-infographic-illustrates-the-stress-of-prolonged-sitting-importance-of-getting-up. Accessed 29 Dec 2013.
Munz, F. W., & Beatty, D. D. (1965). A critical analysis of the visual pigments of salmon and trout. Vision Research, 5, 1–17.
Roth, W.-M. (2001). “Authentic science”: Enculturation into the conceptual blind spots of a discipline. British Educational Research Journal, 27, 5–27.
Roth, W.-M. (2005). Making classifications (at) work: Ordering practices in science. Social Studies of Science, 35, 581–621.
Roth, W.-M. (2008). Constructing community health and safety. Municipal Engineer, 161, 83–92.
Roth, W.-M., & Bowen, G. M. (2001). Of disciplined minds and disciplined bodies. Qualitative Sociology, 24, 459–481.
Roth, W.-M., & Bowen, G. M. (2003). When are graphs ten thousand words worth? An expert/expert study. Cognition and Instruction, 21, 429–473.
Suchman, L. A. (1987). Plans and situated actions: The problem of human-machine communication. Cambridge: Cambridge University Press.
Suzuki, D. (1989). Inventing the future: Reflections on science, technology, and nature. Toronto: Stoddart.
Temple, S. E., Plate, E. M., Ramsden, S., Haimberger, T. J., Roth, W.-M., & Hawryshyn, C. W. (2006). Seasonal cycle in vitamin A1/A2-based visual pigment composition during the life history of coho salmon (Oncorhynchus kisutch). Journal of Comparative Physiology A: Sensory, Neural, and Behavioral Physiology, 192, 301–313.
Temple, S. E., Ramsden, S. D., Haimberger, T. J., Veldhoen, K. M., Veldhoen, N. J., Carter, N. L., Roth, W.-M., & Hawryshyn, C. W. (2008). Effects of exogenous thyroid hormones on visual pigment composition in coho salmon (Oncorhynchus kisutch). Journal of Experimental Biology, 211, 2134–2143.
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Roth, WM. (2014). Uncertainties in/of Data Generation. In: Uncertainty and Graphing in Discovery Work. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7009-6_3
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