The Analytic Versus Representational Theory of Measurement: A Philosophy of Science Perspective

Measurement Science Review 8 (6):129-146 (2008)

Authors
Vadim Batitsky
St. John's University
Abstract
In this paper we motivate and develop the analytic theory of measurement, in which autonomously specified algebras of quantities (together with the resources of mathematical analysis) are used as a unified mathematical framework for modeling (a) the time-dependent behavior of natural systems, (b) interactions between natural systems and measuring instruments, (c) error and uncertainty in measurement, and (d) the formal propositional language for describing and reasoning about measurement results. We also discuss how a celebrated theorem in analysis, known as Gelfand representation, guarantees that autonomously specified algebras of quantities can be interpreted as algebras of observables on a suitable state space. Such an interpretation is then used to support (i) a realist conception of quantities as objective characteristics of natural systems, and (ii) a realist conception of measurement results (evaluations of quantities) as determined by and descriptive of the states of a target natural system. As a way of motivating the analytic approach to measurement, we begin with a discussion of some serious philosophical and theoretical problems facing the well-known representational theory of measurement. We then explain why we consider the analytic approach, which avoids all these problems, to be far more attractive on both philosophical and theoretical grounds.
Keywords measuring process  quantity algebra  observables
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References found in this work BETA

The Scientific Image.Michael Friedman - 1982 - Journal of Philosophy 79 (5):274-283.
Abstract Measurement Theory.Louis Narens - 1988 - Synthese 76 (1):179-182.
Basic Measurement Theory.Patrick Suppes & Joseph Zinnes - 1963 - In D. Luce (ed.), Journal of Symbolic Logic. John Wiley & Sons.. pp. 1--1.

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Citations of this work BETA

On Thinking (and Measurement).Raymond Aaron Younis - 2013 - In R. Scott Webster Steven A. Stolz (ed.), Measuring up in education. Melbourne: PESA. pp. 255-267.

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