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  1. The Complementarity of Psychometrics and the Representational Theory of Measurement.Elina Vessonen - 2020 - British Journal for the Philosophy of Science 71 (2):415-442.
    Psychometrics and the representational theory of measurement are widely used in social scientific measurement. They are currently pursued largely in isolation from one another. I argue that despite their separation in practice, RTM and psychometrics are complementary approaches, because they can contribute in complementary ways to the establishment of what I argue is a crucial measurement property, namely, representational interpretability. Because RTM and psychometrics are complementary in the establishment of representational interpretability, the current separation of measurement approaches is unfounded. 1Introduction2Two (...)
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  • Old and New Problems in Philosophy of Measurement.Eran Tal - 2013 - Philosophy Compass 8 (12):1159-1173.
    The philosophy of measurement studies the conceptual, ontological, epistemic, and technological conditions that make measurement possible and reliable. A new wave of philosophical scholarship has emerged in the last decade that emphasizes the material and historical dimensions of measurement and the relationships between measurement and theoretical modeling. This essay surveys these developments and contrasts them with earlier work on the semantics of quantity terms and the representational character of measurement. The conclusions highlight four characteristics of the emerging research program in (...)
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  • Algorithmic Measurement Procedures.Aldo F. G. Solis-Labastida & Jorge G. Hirsch - 2020 - Foundations of Physics 50 (8):749-763.
    Measurements are shown to be processes designed to return figures: they are effective. This effectivity allows for a formalization as Turing machines, which can be described employing computation theory. Inspired in the halting problem we draw some limitations for measurement procedures: procedures that verify if a quantity is measured cannot work in every case.
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  • Clinical outcome measurement: Models, theory, psychometrics and practice.Leah McClimans, John Browne & Stefan Cano - 2017 - Studies in History and Philosophy of Science Part A 65:67-73.
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  • The quantification of intelligence in nineteenth-century craniology: an epistemology of measurement perspective.Michele Luchetti - 2022 - European Journal for Philosophy of Science 12 (4):1-29.
    Craniology – the practice of inferring intelligence differences from the measurement of human skulls – survived the dismissal of phrenology and remained a widely popular research program until the end of the nineteenth century. From the 1970s, historians and sociologists of science extensively focused on the explicit and implicit socio-cultural biases invalidating the evidence and claims that craniology produced. Building on this literature, I reassess the history of craniological practice from a different but complementary perspective that relies on recent developments (...)
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  • Beyond the metrological viewpoint.Jean Baccelli - 2020 - Studies in History and Philosophy of Science Part A 1:56-61.
    The representational theory of measurement has long been the central paradigm in the philosophy of measurement. Such is not the case anymore, partly under the influence of the critique according to which RTM offers too poor descriptions of the measurement procedures actually followed in science. This can be called the metrological critique of RTM. I claim that the critique is partly irrelevant. This is because, in general, RTM is not in the business of describing measurement procedures, be it in idealized (...)
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  • Measurement in Science.Eran Tal - 2015 - Stanford Encyclopedia of Philosophy.
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  • The Analytic Versus Representational Theory of Measurement: A Philosophy of Science Perspective.Zoltan Domotor & Vadim Batitsky - 2008 - Measurement Science Review 8 (6):129-146.
    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 (...)
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