Abstract
This chapter presents a pragmatic definition of measurement as an activity of classification, ordination, or quantification of a set of elements according to a model of a relevant attribute in service of a larger goal. Each element of this definitions is discussed in detail, making the case for the advantages of conceptualizing measurement in this way.
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Notes
- 1.
What about counting? From this ppm, there would not be an Aristotelian distinction between discrete and continuous quantities, therefore there would be no need to exclude a priori counting as a form of measurement.
- 2.
One difficulty not often discussed among proponents of the rechristening of some practices as “assessment” instead of “measurement” is the assumption that a comparable word at that level of generality exists in every language. This is by no means a given, and at least in Spanish, there is no separate word for “assessment” aside from words like medición, evaluación, and valoración that, respectively, would correspond to measurement, evaluation, and valuation.
- 3.
A measuring transducer is defined in the vim as a devise, used in measurement, that provides an output quantity having a specified relation to the input quantity (Joint Committee for Guides in Metrology 2012).
- 4.
Especially given Rorty’s panrelational stance, where absent the idea of essential features, “there is nothing to be known about [objects] except an initially large, and forever expandable, web of relations to other objects. Everything that can serve as the term of a relation can be dissolved into another set of relations, and so on for ever. There are, so to speak, relations all the way down, all the way up, and all the way out in every direction: you never reach something which is not just one more nexus of relations.” (pp. 53–54).
- 5.
Another revision to Box’ famous quote, made in an akin spirit but from a different line of argumentation, was posed by Tarpey (2009), who proposes that “All models are right, [but] most are useless”.
- 6.
On a personal note, being “colorblind” myself I have learned the hard way not to make those kinds of statements about color.
- 7.
An example of this controversy was the debate generated by the introduction of Consequential Validity as part of the 1999 Standards for Educational and Psychological Testing. See Sect. 5.1 for a discussion on this point.
- 8.
Although some, like Hand (2004) for example, insist that pragmatic criteria are limited to prediction, there is in principle no reason for such limitation. A pragmatic perspective can seek, for instance, manipulation or explanation.
- 9.
There is no current English translation of this book. I thank Rebecca Freund for kindly translating the relevant passages discussed here.
- 10.
In the original French Binet uses the word classement, which can mean, depending of the context either classification or ordering, and the context of this passage seems to be used in this last sense.
- 11.
This quote was brought to my attention by the detailed analysis that Michell (2012b) makes of it and its relation to the concept of heterogeneous orders, although he draws markedly different conclusions from it.
- 12.
In the original French this quote also uses the word classement, but in this case the English translation treats it as “classification” instead of “ordering.” In light of the omitted footnote and the overall context, it is more likely that Binet meant “ordering” instead.
References
Adams, E. W. (1966). On the nature and purpose of measurement. Synthese, 16(2), 125–169.
Aera, Apa, & Ncme. (1999). Standards for educational and psychological testing. Washington, DC: American Psychological Association.
Aera, Apa, & Ncme. (2014). Standards for educational and psychological testing. Washington, DC: American Psychological Association.
Allport, G. W. (1935). Attitudes. In C. Murchison (Ed.), A handbook of social psychology (pp. 798–844). Worcester, MA: Clark University Press.
Binet, A. (1900). La suggestibilité. Paris: Schleicher frères.
Binet, A., & Simon, T. (1916). The development of intelligence in children (E. Kite, Trans.). Baltimore: Williams & Wilkins Company.
Birnbaum, A. (1968). Some latent trait models and their use in inferring an examinee’s ability. In F. M. Lord & M. R. Novick (Eds.), Statistical theories of mental test scores (pp. 395–479). Reading, MA: Addison-Wesley.
Boring, E. G. (1920). The logic of the normal law of error in mental measurement. The American Journal of Psychology, 31(1), 1–33.
Boumans, M. (2001). Measure for measure: How economists model the world into numbers. Social Research, 68(2), 427–453.
Box, G. E. P., & Draper, N. R. (1987). Empirical model-building and response surfaces. New York: Wiley.
Campbell, N. R. (1920). Physics: The elements. Cambridge: University Press.
Carroll, L. (1893). Sylvie and Bruno concluded. London: Macmillan and Co.
Chang, H. (1995). Circularity and reliability in measurement. Perspectives on Science, 3, 153–172.
Churchman, C. W. (1959). Why measure. In C. W. Churchman & P. Ratoosh (Eds.), Measurement: Definitions and theories. London: John Wiley & Sons.
Cliff, N., & Keats, J. A. (2003). Ordinal measurement in the behavioral sciences. Mahwah, NJ: Lawrence Erlbaum Associates.
Duncan, O. D. (1984). Notes on social measurement: Historical and critical. New York: Russell Sage Foundation.
Franklin, W. (1903). Popular Science. Science, 17(418), 8–15.
Goodman, N. (1970). Seven strictures on similarity. In L. Foster & J. Swanson (Eds.), Experience and Theory (pp. 19–29). Amherst: University of Massachusetts Press.
Goodman, N. (1975). Words, works, worlds. Erkenntnis, 57–73.
Hacking, I. (2007). On not being a pragmatist: Eight reasons and a cause. In New pragmatists (pp. 32–49). New York: Oxford University Press.
Hagenaars, J. A., & McCutcheon, A. L. (2002). Applied latent class analysis. New York: Cambridge University Press.
Hand, D. J. (2004). Measurement theory and practice. London: Arnold.
Joint Committee for Guides in Metrology. (2012). The international vocabulary of metrology – Basic and general concepts and associated terms ( vim ) (3rd ed.). Paris: Bureau International des Poids et Mesures.
Kuhn, T. S. (1961). The function of measurement in modern physical science. ISIS, 52(2), 161–193.
Lakoff, G., & Johnson, M. (1999). Philosophy in the flesh: The embodied mind and its challenge to Western thought. New York: Basic Books.
Lazarsfeld, P. F., & Henry, N. W. (1968). Latent structure analysis. Boston: Houghton Mifflin Company.
Lord, F. M., & Novick, M. R. (1968). Statistical theories of mental test scores. Reading, MA: Addison-Wesley Pub. Co.
Mari, L. (2003). Epistemology of measurement. Measurement, 34(1), 17–30.
Michell, J. (1997b). Quantitative science and the definition of measurement in psychology. British Journal of Psychology, 88(3), 355–383.
Michell, J. (2003). Pragmatism, positivism and the quantitative imperative. Theory & Psychology, 13(1), 45–52.
Michell, J. (2008b). The measure of psychometrics — Review: Denny Borsboom, measuring the mind: Conceptual issues in contemporary psychometrics. Theory & Psychology, 18(1), 135–137.
Michell, J. (2011). Qualitative research meets the ghost of Pythagoras. Theory & Psychology, 21(2), 241–259.
Michell, J. (2012b). Alfred Binet and the concept of heterogeneous orders. Frontiers in psychology, 3(261), 1–8.
Minsky, M. (1968). Matter, Mind and Models. In M. Minsky (Ed.), Semantic Information Processing (pp. 425–432). Cambridge, MA: MIT Press.
Rasch, G. (1960/1980). Probabilistic models for some intelligence and attainment tests. Chicago: University of Chicago Press (Original work published 1960).
Rorty, R. (1999). Philosophy and social hope. London: Penguin.
Sherry, D. (2011). Thermoscopes, thermometers, and the foundations of measurement. Studies in History and Philosophy of Science Part A, 42(4), 509–524.
Skrondal, A., & Rabe-Hesketh, S. (2004). Generalized latent variable modeling: Multilevel, longitudinal, and structural equation models. Boca Raton, FL: Chapman & Hall/CRC.
Stevens, S. S. (1946). On the theory of scales of measurement. Science, 103(2684), 677–680.
Tal, E. (2013). Old and new problems in philosophy of measurement. Philosophy Compass, 8(12), 1159–1173.
Tarpey, T. (2009). All Models are Right… most are useless. http://andrewgelman.com/wp-content/uploads/2012/03/tarpey.pdf
Tartaglia, J. (2007). Routledge philosophy guidebook to Rorty and the mirror of nature. London, New York: Routledge.
Teller, P. (2001). Twilight of the perfect model model. Erkenntnis, 55(3), 393–415.
Trout, J. D. (1998). Measuring the intentional world realism, naturalism, and quantitative methods in the behavioral sciences. New York: Oxford University Press.
Van Fraassen, B. C. (2008). Scientific representation: Paradoxes of perspective. New York: Oxford University Press.
Varela, F. J., Thompson, E., & Rosch, E. (1991). The embodied mind: Cognitive science and human experience. Cambridge, MA: MIT Press.
Wilson, M. (2013). Using the concept of a measurement system to characterize measurement models used in psychometrics. Measurement, 46(9), 3766–3774.
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Torres Irribarra, D. (2021). A Pragmatic Perspective of Measurement. In: A Pragmatic Perspective of Measurement. SpringerBriefs in Psychology(). Springer, Cham. https://doi.org/10.1007/978-3-030-74025-2_4
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