Graduate studies at Western
Measurement 42 (2):241-253 (2009)
|Abstract||Measurement in soft systems generally cannot exploit physical sensors as data acquisition devices. The emphasis in this case is instead on how to choose the appropriate indicators and to combine their values so to obtain an overall result, interpreted as the value of a property, i.e., the measurand, for the system under analysis. This paper aims at discussing the epistemological conditions of the claim that such a process is a measurement, and performance evaluation is the case introduced to support the analysis, performed in systematic comparison with the paradigm of measurement of physical quantities. Some background questions arising here are: – Are the chosen indicators appropriate performance indicators? – Do such indicators convey complete and non-redundant information on performance? – Does the chosen combination rule generate results suitably interpretable as performance values? And enlarging the focus: – Does the obtained value specifically convey information on the system under analysis, instead of some different entity (typically including the subject who is evaluating)? Operatively: would different subjects evaluate the same system in the same way? i.e., is the obtained information objective? – Does the obtained value convey information that is interpretable in the same way by different subjects? Operatively: would different subjects who have agreed on a decision procedure make the same decision from the same performance information? i.e., is the obtained information intersubjective? Any well founded positive answers to these questions significantly support a structural interpretation of measurement encompassing both physical and soft measurement.|
|Keywords||Foundations of measurement Measurement in soft systems Models in measurement|
|Categories||categorize this paper)|
|Through your library||Configure|
Similar books and articles
Alessandro Giordani & Luca Mari (2012). Measurement, Models, and Uncertainty. IEEE Transactions on Instrumentation and Measurement 61 (8):2144 - 2152.
Ludwik Finkelstein (1994). Measurement and Instrumentation Science. An Analytical Review. Measurement 14 (1):3-14.
Luca Mari (2005). The Problem of Foundations of Measurement. Measurement 38 (4):259-266.
Luca Mari (2003). Epistemology of Measurement. Measurement 34 (1):17-30.
Luca Mari (2000). Beyond the Representational Viewpoint: A New Formalization of Measurement. Measurement 27 (2):71-84.
Aldo Frigerio, Alessandro Giordani & Luca Mari (2010). Outline of a General Model of Measurement. Synthese 175 (2):123-149.
Ludwik Finkelstein (2003). Widely, Strongly and Weakly Defined Measurement. Measurement 34 (1):39-48.
Luca Mari & Sergio Sartori (2007). A Relational Theory of Measurement: Traceability as a Solution to the Non-Transitivity of Measurement Results. Measurement 40 (2):233-242.
Ludwik Finkelstein (2009). Widely-Defined Measurement. An Analysis of Challenges. Measurement 42 (9):1270–1277.
Giovanni Rossi (2006). A Probabilistic Theory of Measurement. Measurement 39:34-50.
Zoltan Domotor & Vadim Batitsky (2008). The Analytic Versus Representational Theory of Measurement: A Philosophy of Science Perspective. Measurement Science Review 8 (6):129-146.
Ludwik Finkelstein (1984). A Review of the Fundamental Concepts of Measurement. [REVIEW] Measurement 2 (1):25-34.
Louis Narens (1974). Measurement Without Archimedean Axioms. Philosophy of Science 41 (4):374-393.
Zhengjun Xi & Yongming Li (2013). Quantum and Classical Correlations in Quantum Measurement. Foundations of Physics 43 (3):285-293.
Sorry, there are not enough data points to plot this chart.
Added to index2011-12-14
Total downloads1 ( #292,381 of 739,350 )
Recent downloads (6 months)1 ( #61,538 of 739,350 )
How can I increase my downloads?