2020
DOI: 10.1016/j.cognition.2020.104182
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Reverse engineering cash: Coin designs mark out high value differentials and coin sizes track values logarithmically

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Cited by 4 publications
(2 citation statements)
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“…Two main lines of research have investigated informativeness in the conventions that bind meanings to signals. One considers the costs and benefits of informativeness: more precise words tend to be longer and more costly to produce and process [1,3,5], partly explaining why informativeness is so unevenly distributed among words (this reasoning also applies to nonlinguistic symbols, such as coin designs [6]). The second research tradition considers diachronic changes in word meanings: historical trends that lead to semantic narrowing, or the opposite, semantic broadening [7].…”
Section: Cultural Evolution Of Precise and Consensual Semantic Convenmentioning
confidence: 99%
“…Two main lines of research have investigated informativeness in the conventions that bind meanings to signals. One considers the costs and benefits of informativeness: more precise words tend to be longer and more costly to produce and process [1,3,5], partly explaining why informativeness is so unevenly distributed among words (this reasoning also applies to nonlinguistic symbols, such as coin designs [6]). The second research tradition considers diachronic changes in word meanings: historical trends that lead to semantic narrowing, or the opposite, semantic broadening [7].…”
Section: Cultural Evolution Of Precise and Consensual Semantic Convenmentioning
confidence: 99%
“…On the other hand, coins are representations of amounts of money that differ in physical features such as size and colour. It has been observed that, in general, coins are designed to favour the distinctiveness between them and the monetary value they reflect (e.g., Pavlek et al, 2020 ). Regarding the physical features of coins, several studies have evaluated the relationship between size and monetary value (Fitousi, 2010 ; Goldman et al, 2012 ; Hasegawa, 2020 ; Peetz & Soliman, 2016 ).…”
Section: Introductionmentioning
confidence: 99%