<p>Recent work in philosophy of measurement has converged on a "theory-dependence consensus”, according to which measurement reliability requires sophisticated theoretical scaffolding. This consensus has been largely shaped by case studies from physics and high-precision metrology. This paper questions whether this consensus adequately captures measurement practices in biology, where researchers often operate under significant uncertainty about their target phenomena. Through detailed historical analysis of early electrophysiological research—from Carlo Matteucci through Emil du Bois-Reymond, Hermann von Helmholtz, and Ludimar Hermann—I examine how quantitative measurement practices emerged under theoretical uncertainty. The cases reveal recurring patterns including productive theoretical inadequacy and instrumental constraint-driven discovery, supporting an analytical framework that distinguishes multiple levels of theoretical involvement in measurement. Building on these cases, I argue that biological measurement practices function productively as strategies for causal discovery, and theoretically inadequate frameworks prove epistemically valuable by structuring empirical inquiry to reveal previously unrecognised causal factors.</p>

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Measurement under uncertainty: theory-measurement relations in early electrophysiological research

  • Maria Şerban

摘要

Recent work in philosophy of measurement has converged on a "theory-dependence consensus”, according to which measurement reliability requires sophisticated theoretical scaffolding. This consensus has been largely shaped by case studies from physics and high-precision metrology. This paper questions whether this consensus adequately captures measurement practices in biology, where researchers often operate under significant uncertainty about their target phenomena. Through detailed historical analysis of early electrophysiological research—from Carlo Matteucci through Emil du Bois-Reymond, Hermann von Helmholtz, and Ludimar Hermann—I examine how quantitative measurement practices emerged under theoretical uncertainty. The cases reveal recurring patterns including productive theoretical inadequacy and instrumental constraint-driven discovery, supporting an analytical framework that distinguishes multiple levels of theoretical involvement in measurement. Building on these cases, I argue that biological measurement practices function productively as strategies for causal discovery, and theoretically inadequate frameworks prove epistemically valuable by structuring empirical inquiry to reveal previously unrecognised causal factors.