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Abstract

We present a measure called i-bar, which is the inverse of the mid-range derived from data on trials-to-criterion. We interpret this measure as a conjoint measurement scale, permitting evaluation of: (1) the sensitivity of the principal performance measure (which is used to set the metric for trials to criterion), (2) the learnability of the work method (i.e., the goodness of the software tool), and (3) the resilience of the work method. It is possible to mathematically model such order statistics, and derive methods for estimating likelihoods. This proposal involves novel ways of thinking about statistical analysis for discrete non-Gaussian distributions. The method we present should be applicable to the study of the effects of any form of training, and any form of intervention, whether to improve legacy work methods or create new cognitive work systems.

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The Metrics Problem in the Study of Cognitive Work and a Proposal for a Family of Solutions

Abstract

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