Measurement Accuracy Realism

Abstract

This paper challenges “traditional measurement-accuracy realism”, according to which there are in nature quantities of which concrete systems have definite values. An accurate measurement outcome is one that is close to the value for the quantity measured. For a measurement of the temperature of some water to be accurate in this sense requires that there be this temperature. But there isn’t. Not because there are no quantities “out there in nature” but because the term ‘the temperature of this water’ fails to refer owing to idealization and failure of specificity in picking out concrete cases. The problems can be seen as an artifact of vagueness, and so doing facilitates applying Eran Tal’s robustness account of measurement accuracy to suggest an attractive way of understanding vagueness in terms of the function of idealization, a way that sidesteps the problems of higher order vagueness and that shows how idealization provides a natural generalization of what it is to be vague.

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Citations of this work

Data models, representation and adequacy-for-purpose.Alisa Bokulich & Wendy Parker - 2021 - European Journal for Philosophy of Science 11 (1):1-26.
Measurement in Science.Eran Tal - 2015 - Stanford Encyclopedia of Philosophy.
Models as Felicitous Falsehoods.Catherine Elgin - 2022 - Principia: An International Journal of Epistemology 26 (1):7-23.
Worldly imprecision.Michael E. Miller - 2020 - Philosophical Studies 178 (9):2895-2911.
Making worlds with symbols.Paul Teller - 2018 - Synthese 198 (Suppl 21):5015-5036.

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