Search

It is widely acknowledged that opaque orthographies place additional demands on learning, often requiring many years to fully acquire. It is less widely recognized, however, that such opacity may offer certain benefits in the context of reading. For example, heterographic homophones such as ⟨knight⟩ and ⟨night⟩ (words that sound the same but which are spelled differently) impose additional costs in learning but reduce ambiguity in reading. Here, we consider the possibility that-left to evolve freely-writing systems will sometimes choose to forego some simplicity for the sake of informativeness when there is functional pressure to do so. We investigate this hypothesis by simulating the evolution of orthography as it is transmitted from one generation to the next, both with and without a communicative pressure for ambiguity avoidance. In addition, we consider two mechanisms by which informative heterography might be selected for: differentiation, in which new spellings are created to differentiate meaning (e.g., ⟨lite⟩ vs. ⟨light⟩), and conservation, in which heterography arises as a byproduct of sound change (e.g., ⟨meat⟩ vs. ⟨meet⟩). Under pressure from learning alone, orthographic systems become transparent, but when combined with communicative pressure, they tend to favor some additional informativeness. Nevertheless, our findings also suggest that, in the long term, simpler, transparent spellings may be preferred in the absence of top-down explicit teaching., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Recent research has shown that semantic category systems, such as color and kinship terms, find an optimal balance between simplicity and informativeness. We argue that this situation arises through pressure for simplicity from learning and pressure for informativeness from communicative interaction, two distinct pressures that often (but not always) pull in opposite directions. Another account argues that learning might also act as a pressure for informativeness, that learners might be biased toward inferring informative systems. This results in two competing hypotheses about the human inductive bias. We formalize these competing hypotheses in a Bayesian iterated learning model in order to simulate what kinds of languages are expected to emerge under each. We then test this model experimentally to investigate whether learners' biases, isolated from any communicative task, are better characterized as favoring simplicity or informativeness. We find strong evidence to support the simplicity account. Furthermore, we show how the application of a simplicity principle in learning can give the impression of a bias for informativeness, even when no such bias is present. Our findings suggest that semantic categories are learned through domain-general principles, negating the need to posit a domain-specific mechanism., (Copyright © 2020 Elsevier B.V. All rights reserved.)