The empirical measurement of mental effort is an important problem in the cognitive sciences. Recently, researchers have adopted econometric tools to attempt to characterize mental effort in terms of monetary costs foregone. Such efforts yield a very helpful calculation device - a money utility of mental effort. However, since the opportunity cost of applying mental effort in any given situation is measured with respect to time rather than money in most ecologically reasonable settings, it is even more desirable to obtain a measure of the time utility of mental effort. In the absence of direct measurements of men- tal effort, such a task has proved econometrically challenging. We use a recently developed direct measure of mental effort to characterize its time utility, finding that it is approximately linear in effort. We discuss some implications of this result for current theories of mental effort, as well as for practical applications.

It is intuitive to believe that humans take considerations of mental effort into account when making decisions. However, it has proved difficult to differentiate theories of mental effort in the absence of direct measurements of this psychological construct. Existing measurements of mental effort using response times and revealed preferences have low reliability. In this paper, we present a new experimental task - selecting between visuomotor lotteries using eye-tracking for sampling lotteries - that enables direct measurement of mental effort. Unlike response time-based measures, effort measurements in this task are not confounded by actual effort allocation. Unlike revealed preference-based measures, effort measurements in this task are acquired on a natural scale unitized by automatic visual selection processes. We also report results from a simple experiment conducted using this task, which reproduce existing findings of costly effort-aversion, and also demonstrate adaptive adjustment of mental effort.

A wealth of developmental evidence suggests that children es-sentialise natural kind but not artifact categories, and that bothadults and children use generic language less with artifacts aswell (Gelman, 2003). Here we further explore the latter resultusing a novel model for generic identification. We apply ourmodel to a much larger dataset than before, consisting of 26CHILDES corpora of naturalistic speech involving children ata variety of ages and in a variety of contexts. We found noconsistent preference for generic usage in animates over arti-facts. Follow-up analyses indicate that this result was probablydriven by our inclusion of a wider variety of nouns into ourdataset than previous work.