68
sure” (except in the idiomatic term “material measure”) to reduce ambiguity,
22
and
its adoption of “measurement result” to designate the outcome of the process. This
is the lexical choice that we make here too.
The operational and conceptual issues discussed in this chapter provide a basis
for our analysis of philosophical perspectives on measurement, to which the next
chapter is devoted.
References
Bevington, P. R. (1969). Data reduction and error analysis for the physical sciences. New York:
McGraw-Hill.
Bunge, M. (1973). On confusing ‘measure’ with ‘measurement’ in the methodology of behavioral
science. In M. Bunge (Ed.), The methodological unity of science (pp. 105–122). Dordrecht:
Reidel.
Chang, H. (2007). Inventing temperature—Measurement and scientific progress. Oxford: Oxford
University Press.
Ellis, B. (1968). Basic concepts of measurement. Cambridge: Cambridge University Press.
Euclid’s Elements of geometry, the Greek text of J.L. Heiberg (1883–1885) edited, and provided
with a modern English translation, by Richard Fitzpatrick (2008). Retrieved from farside.
ph.utexas.edu/Books/Euclid/Euclid.html
Euler, L. (1765). Elements of algebra. Translated into English by J. Hewlett, London.
Ferrero, A., & Salicone, S. (2006). Fully comprehensive mathematical approach to the expression of uncertainty in measurement. IEEE Transactions on Instrumentation and Measurement,
55(3), 706–712.
Giordani, A., & Mari, L. (2014). Modeling measurement: Error and uncertainty. In M. Boumans,
G. Hon, & A. C. Petersen (Eds.), Error and uncertainty in scientific practice (pp. 79–86).
London: Pickering & Chatto.
Hacking, I. (1975). The emergence of probability—A philosophical study of early ideas about
probability, induction and statistical inference. Cambridge: Cambridge University Press.
Hacking, I. (1990). The taming of chance. Cambridge: Cambridge University Press.
22 In reference to the black box model we have just discussed, the noun “measure” is sometimes
used to refer to each of the three elements of the model: the input property, the process, and the
output value. Just as an example, Isaac Newton famously began his Principia with the following
two definitions: “Definition I. The Quantity of Matter is the measure of the same, arising from its
density and bulk conjunctly. Definition II. The Quantity of Motion is the measure of the same,
arising from the velocity and quantity of matter conjunctly” (1724: p. 1). Here the concepts and appear to be equivalent. Very interesting on this matter is the following quote
from Leonhard Euler: “Whatever is capable of increase or diminution is called magnitude, or
quantity. […] Mathematics, in general, is the science of quantity; or, the science which investigates
the means of measuring quantity. […] Now, we cannot measure or determine any quantity, except
by considering some other quantity of the same kind as known, and pointing out their mutual relation. […] So that the determination, or the measure of magnitude of all kinds, is reduced to this: fix
at pleasure upon any one known magnitude of the same species with that which is to be determined, and consider it as the measure or unit; then, determine the proportion of the proposed
magnitude to this known measure. This proportion is always expressed by numbers; so that a
number is nothing but the proportion of one magnitude to another arbitrarily assumed as the unit”
(1765: pp. 1–2).
3 Technical and cultural contexts for measurement systems
sure” (except in the idiomatic term “material measure”) to reduce ambiguity,
22
and
its adoption of “measurement result” to designate the outcome of the process. This
is the lexical choice that we make here too.
The operational and conceptual issues discussed in this chapter provide a basis
for our analysis of philosophical perspectives on measurement, to which the next
chapter is devoted.
References
Bevington, P. R. (1969). Data reduction and error analysis for the physical sciences. New York:
McGraw-Hill.
Bunge, M. (1973). On confusing ‘measure’ with ‘measurement’ in the methodology of behavioral
science. In M. Bunge (Ed.), The methodological unity of science (pp. 105–122). Dordrecht:
Reidel.
Chang, H. (2007). Inventing temperature—Measurement and scientific progress. Oxford: Oxford
University Press.
Ellis, B. (1968). Basic concepts of measurement. Cambridge: Cambridge University Press.
Euclid’s Elements of geometry, the Greek text of J.L. Heiberg (1883–1885) edited, and provided
with a modern English translation, by Richard Fitzpatrick (2008). Retrieved from farside.
ph.utexas.edu/Books/Euclid/Euclid.html
Euler, L. (1765). Elements of algebra. Translated into English by J. Hewlett, London.
Ferrero, A., & Salicone, S. (2006). Fully comprehensive mathematical approach to the expression of uncertainty in measurement. IEEE Transactions on Instrumentation and Measurement,
55(3), 706–712.
Giordani, A., & Mari, L. (2014). Modeling measurement: Error and uncertainty. In M. Boumans,
G. Hon, & A. C. Petersen (Eds.), Error and uncertainty in scientific practice (pp. 79–86).
London: Pickering & Chatto.
Hacking, I. (1975). The emergence of probability—A philosophical study of early ideas about
probability, induction and statistical inference. Cambridge: Cambridge University Press.
Hacking, I. (1990). The taming of chance. Cambridge: Cambridge University Press.
22 In reference to the black box model we have just discussed, the noun “measure” is sometimes
used to refer to each of the three elements of the model: the input property, the process, and the
output value. Just as an example, Isaac Newton famously began his Principia with the following
two definitions: “Definition I. The Quantity of Matter is the measure of the same, arising from its
density and bulk conjunctly. Definition II. The Quantity of Motion is the measure of the same,
arising from the velocity and quantity of matter conjunctly” (1724: p. 1). Here the concepts
from Leonhard Euler: “Whatever is capable of increase or diminution is called magnitude, or
quantity. […] Mathematics, in general, is the science of quantity; or, the science which investigates
the means of measuring quantity. […] Now, we cannot measure or determine any quantity, except
by considering some other quantity of the same kind as known, and pointing out their mutual relation. […] So that the determination, or the measure of magnitude of all kinds, is reduced to this: fix
at pleasure upon any one known magnitude of the same species with that which is to be determined, and consider it as the measure or unit; then, determine the proportion of the proposed
magnitude to this known measure. This proportion is always expressed by numbers; so that a
number is nothing but the proportion of one magnitude to another arbitrarily assumed as the unit”
(1765: pp. 1–2).
3 Technical and cultural contexts for measurement systems