The evaluation of measurement uncertainties and its epistemological ramifications

Abstract

The way metrologists conceive of measurement has undergone a major shift in the last two decades. This shift can in great part be traced to a change in the statistical methods used to deal with the expression of measurement results, and, more particularly, with the calculation of measurement uncertainties. Indeed, as we show, the incapacity of the frequentist approach to the calculus of uncertainty to deal with systematic errors has prompted the replacement of the customary frequentist methods by fully Bayesian procedures. The epistemological ramifications of the Bayesian approach merge with a deep empiricist mood tantamount to an "epistemic turn": measurement results are analysed in terms of degrees of belief, and central concepts such as error and accuracy are called into question. We challenge the perspective entailed by this epistemic turn: we insist on the centrality of the concepts of error and accuracy by underlining the intentional character of measurement that is intimately linked to the process of correction of experimental data. We further circumvent the difficulties posed by the classical analysis of measurement by stressing the social rather than the epistemic dimension of measurement activities.

On the meaning of measurement uncertainty

“…Such a choice allows for the existence of different frameworks for the analysis and interpretation of measurement uncertainty. This could be fitting considering the context in which the VIM2&3 were composed: intense debates have emerged within the community of metrologists during these past decades with regard to the nature of the probabilities and the statistical methods to be used in the context of measurement uncertainty evaluation [8].…”

“…However, the amended VIM1 proposal stumbles upon a major problem: it can only account for error sources that have been identified 8 . The actual "success rate" of a measurement process is unknown: it can only be predicted under a set of hypotheses, including specific statistical models, and the hypothesis that no unknown systematic error 5 One might argue that the definition only makes measurement uncertainty an "estimate" here.…”

About a New Concept Diagram for the Measurement Process and Related Terms

“…However, that is not the "experimental model" (or descriptive model [6]), in general needing to be much more complicated and that is specific for each experimental setup. A generic one is shown in Fig.…”

Data inter-comparisons in the context of the knowledge-gaining process: an overview

“…In other words, it is, or should be, recognized as a quantity having a current recognizable meaning for the specific community. In the jargon of science philosophers, this means that it should be projected onto a "social framework" [5]. In the scientific experimental context, this means that the measurand model must be of the "prescriptive" type, meaning "giving directions or injunctions" [6], which does not always denote the "physical" model.…”