RESUMEN
This article discusses the ways in which nineteenth-century geodesists reflected on precision as an epistemic virtue in their measurement practice. Physical geodesy is often understood as a quintessential nineteenth-century precision science, stimulating advances in instrument making and statistics, and generating incredible quantities of data. Throughout most of the nineteenth century, geodesists indeed pursued their most prestigious research problem - the exact determination of the earth's polar flattening - along those lines. Treating measurement errors as random, they assumed that remaining discordances could be overcome by manufacturing better instruments and extending statistical analysis to a larger amount of data. In the second half of the nineteenth century, however, several German geodesists developed sophisticated methodological critiques of their discipline, in which they diagnosed a too-narrow focus on precision among their peers. On their account, geodesists urgently needed to identify and anticipate the causes of the remaining measurement errors that arose from the earth's little understood interior constitution. While mostly overlooked in the literature, these critiques paved the way for many empirical successes in late nineteenth- and early twentieth-century geodesy, including the first convergent measurements of the earth's polar flattening.
RESUMEN
Derived measurements involve problems of coordination. Conducting them often requires detailed theoretical assumptions about their target, while such assumptions can lack sources of evidence that are independent from these very measurements. In this paper, I defend two claims about problems of coordination. I motivate both by a novel case study on a central measurement problem in the history of physical geodesy: the determination of the earth's ellipticity. First, I argue that the severity of problems of coordination varies according to scientists' predictive and experimental control over perturbations of the measurement process. Second, I identify a methodology by which scientists can solve hard problems of coordination and gradually increase their predictive control over perturbations. I dub this methodology 'operational pluralism' since it is driven by the introduction of alternative measurement operations that involve different physical indicators.
RESUMEN
The development of nineteenth-century geodetic measurement challenges the dominant coherentist account of metric success. Coherentists argue that measurements of a parameter are successful if their numerical outcomes convergence across varying contextual constraints. Aiming at numerical convergence, in turn, offers an operational aim for scientists to solve problems of coordination. Geodesists faced such a problem of coordination between two indicators of the earth's polar flattening, which were both based on imperfect ellipsoid models. While not achieving numerical convergence, their measurements produced novel data that grounded valuable theoretical hypotheses. Consequently, they ought to be regarded as epistemically successful. This insight warrants a dynamic revision of coherentism, which allows to judge the success of a metric based on both its coherence and fruitfulness. On that view, scientific measurement aims to coordinate theoretical definitions and produce novel data and theoretical insights.
RESUMEN
This article develops a constructive criticism of methodological conventionalism. Methodological conventionalism asserts that standards of inductive risk ought to be justified in virtue of their ability to facilitate coordination in a research community. On that view, industry bias occurs when conventional methodological standards are violated to foster industry preferences. The underlying account of scientific conventionality, however, is insufficient for theoretical and practical reasons. Conventions may be justified in virtue of their coordinative functions, but often qualify for posterior empirical criticism as research advances. Accordingly, industry bias does not only threaten existing conventions but may impede their empirically warranted improvement if they align with industry preferences. My empiricist account of standards of inductive risk avoids such a problem by asserting that conventional justification can be pragmatically warranted but has, in principle, only a provisional status. Methodological conventions, therefore, should not only be defended from preference-based infringements of their coordinative function but ought to be subjected to empirical criticism.